Retrieving multi-generational stored data in a dispersed storage network

ABSTRACT

A method begins by a processing module a dispersed storage network (DSN) generating, based on a data object name, a first retrieval request for retrieving metadata addressing information, where the first retrieval request is formatted in accordance with a read request format of the DSN. The method continues with the processing module generating, based on retrieved metadata addressing information, a second retrieval request for retrieving metadata, where the second retrieval request is formatted in accordance with the read request format of the DSN. The method continues with the processing module generating, based on retrieved metadata, a third retrieval request for retrieving at least a portion of a data object associated with the data object name, where the third retrieval request is formatted in accordance with the read request format of the DSN.

CROSS REFERENCE TO RELATED PATENTS

The present U.S. Utility Patent Application claims priority pursuant to35 U.S.C. §119(e) to U.S. Provisional Application No. 61/986,361,entitled “ACCESSING METADATA IN A DISPERSED STORAGE NETWORK”, filed Apr.30, 2014, which is hereby incorporated herein by reference in itsentirety and made part of the present U.S. Utility Patent Applicationfor all purposes.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

NOT APPLICABLE

INCORPORATION-BY-REFERENCE OF MATERIAL SUBMITTED ON A COMPACT DISC

NOT APPLICABLE

BACKGROUND OF THE INVENTION

1. Technical Field of the Invention

This invention relates generally to computer networks and moreparticularly to dispersed storage of data and distributed taskprocessing of data.

2. Description of Related Art

Computing devices are known to communicate data, process data, and/orstore data. Such computing devices range from wireless smart phones,laptops, tablets, personal computers (PC), work stations, and video gamedevices, to data centers that support millions of web searches, stocktrades, or on-line purchases every day. In general, a computing deviceincludes a central processing unit (CPU), a memory system, userinput/output interfaces, peripheral device interfaces, and aninterconnecting bus structure.

As is further known, a computer may effectively extend its CPU by using“cloud computing” to perform one or more computing functions (e.g., aservice, an application, an algorithm, an arithmetic logic function,etc.) on behalf of the computer. Further, for large services,applications, and/or functions, cloud computing may be performed bymultiple cloud computing resources in a distributed manner to improvethe response time for completion of the service, application, and/orfunction. For example, Hadoop is an open source software framework thatsupports distributed applications enabling application execution bythousands of computers.

In addition to cloud computing, a computer may use “cloud storage” aspart of its memory system. As is known, cloud storage enables a user,via its computer, to store files, applications, etc., on an Internetstorage system. The Internet storage system may include a RAID(redundant array of independent disks) system and/or a dispersed storagesystem that uses an error correction scheme to encode data for storage.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWING(S)

FIG. 1 is a schematic block diagram of an embodiment of a distributedcomputing system in accordance with the present invention;

FIG. 2 is a schematic block diagram of an embodiment of a computing corein accordance with the present invention;

FIG. 3 is a diagram of an example of a distributed storage and taskprocessing in accordance with the present invention;

FIG. 4 is a schematic block diagram of an embodiment of an outbounddistributed storage and/or task (DST) processing in accordance with thepresent invention;

FIG. 5 is a logic diagram of an example of a method for outbound DSTprocessing in accordance with the present invention;

FIG. 6 is a schematic block diagram of an embodiment of a dispersederror encoding in accordance with the present invention;

FIG. 7 is a diagram of an example of a segment processing of thedispersed error encoding in accordance with the present invention;

FIG. 8 is a diagram of an example of error encoding and slicingprocessing of the dispersed error encoding in accordance with thepresent invention;

FIG. 9 is a diagram of an example of grouping selection processing ofthe outbound DST processing in accordance with the present invention;

FIG. 10 is a diagram of an example of converting data into slice groupsin accordance with the present invention;

FIG. 11 is a schematic block diagram of an embodiment of a DST executionunit in accordance with the present invention;

FIG. 12 is a schematic block diagram of an example of operation of a DSTexecution unit in accordance with the present invention;

FIG. 13 is a schematic block diagram of an embodiment of an inbounddistributed storage and/or task (DST) processing in accordance with thepresent invention;

FIG. 14 is a logic diagram of an example of a method for inbound DSTprocessing in accordance with the present invention;

FIG. 15 is a diagram of an example of de-grouping selection processingof the inbound DST processing in accordance with the present invention;

FIG. 16 is a schematic block diagram of an embodiment of a dispersederror decoding in accordance with the present invention;

FIG. 17 is a diagram of an example of de-slicing and error decodingprocessing of the dispersed error decoding in accordance with thepresent invention;

FIG. 18 is a diagram of an example of a de-segment processing of thedispersed error decoding in accordance with the present invention;

FIG. 19 is a diagram of an example of converting slice groups into datain accordance with the present invention;

FIG. 20 is a diagram of an example of a distributed storage within thedistributed computing system in accordance with the present invention;

FIG. 21 is a schematic block diagram of an example of operation ofoutbound distributed storage and/or task (DST) processing for storingdata in accordance with the present invention;

FIG. 22 is a schematic block diagram of an example of a dispersed errorencoding for the example of FIG. 21 in accordance with the presentinvention;

FIG. 23 is a diagram of an example of converting data into pillar slicegroups for storage in accordance with the present invention;

FIG. 24 is a schematic block diagram of an example of a storageoperation of a DST execution unit in accordance with the presentinvention;

FIG. 25 is a schematic block diagram of an example of operation ofinbound distributed storage and/or task (DST) processing for retrievingdispersed error encoded data in accordance with the present invention;

FIG. 26 is a schematic block diagram of an example of a dispersed errordecoding for the example of FIG. 25 in accordance with the presentinvention;

FIG. 27 is a schematic block diagram of an example of a distributedstorage and task processing network (DSTN) module storing a plurality ofdata and a plurality of task codes in accordance with the presentinvention;

FIG. 28 is a schematic block diagram of an example of the distributedcomputing system performing tasks on stored data in accordance with thepresent invention;

FIG. 29 is a schematic block diagram of an embodiment of a taskdistribution module facilitating the example of FIG. 28 in accordancewith the present invention;

FIG. 30 is a diagram of a specific example of the distributed computingsystem performing tasks on stored data in accordance with the presentinvention;

FIG. 31 is a schematic block diagram of an example of a distributedstorage and task processing network (DSTN) module storing data and taskcodes for the example of FIG. 30 in accordance with the presentinvention;

FIG. 32 is a diagram of an example of DST allocation information for theexample of

FIG. 30 in accordance with the present invention;

FIGS. 33-38 are schematic block diagrams of the DSTN module performingthe example of FIG. 30 in accordance with the present invention;

FIG. 39 is a diagram of an example of combining result information intofinal results for the example of FIG. 30 in accordance with the presentinvention;

FIG. 40A is a schematic block diagram of an embodiment of a dispersedstorage network (DSN) in accordance with the present invention;

FIG. 40B is a schematic block diagram illustrating an embodiment of adeterministic function module utilized to retrieve data in accordancewith the present invention;

FIG. 40C is a flowchart illustrating an example of retrievingmulti-generational stored data in accordance with the present invention;

FIG. 41A is a schematic block diagram of another embodiment of adispersed storage network (DSN) in accordance with the presentinvention;

FIG. 41B is a flowchart illustrating an example of confirming storage ofa data object in accordance with the present invention;

FIGS. 42A and 42B are a schematic block diagram of another embodiment ofa dispersed storage network (DSN) in accordance with the presentinvention;

FIG. 42C is a flowchart illustrating an example of delegating aniterative storage unit access process in accordance with the presentinvention;

FIG. 43A is a schematic block diagram of another embodiment of adispersed storage network (DSN) in accordance with the presentinvention;

FIG. 43B is a flowchart illustrating an example of associating dataaccess resources with an index in accordance with the present invention;

FIG. 44A is a schematic block diagram of another embodiment of adispersed storage network (DSN) in accordance with the presentinvention;

FIG. 44B is a flowchart illustrating an example of updating a dispersedhierarchical index in accordance with the present invention;

FIG. 45A is a schematic block diagram of another embodiment of adispersed storage network (DSN) in accordance with the presentinvention;

FIG. 45B is a schematic block diagram of a plurality of storagegenerations in accordance with the present invention;

FIG. 45C is a flowchart illustrating an example of adding a storagegeneration to a dispersed storage network (DSN) in accordance with thepresent invention;

FIG. 46A is a schematic block diagram of another embodiment of adispersed storage network (DSN) in accordance with the presentinvention;

FIG. 46B is a flowchart illustrating an example of acquiring criticalinformation in accordance with the present invention;

FIGS. 47A and 47B are a schematic block diagram of another embodiment ofa dispersed storage network (DSN) in accordance with the presentinvention;

FIG. 47C is a table illustrating an example of resolving write requestconflicts in accordance with the present invention;

FIG. 47D is a flowchart illustrating an example of resolving writerequest conflicts in accordance with the present invention;

FIG. 48A is a schematic block diagram of another embodiment of adispersed storage network (DSN) in accordance with the presentinvention; and

FIG. 48B is a flowchart illustrating an example of activating a storagegeneration in accordance with the present invention.

DETAILED DESCRIPTION OF THE INVENTION

FIG. 1 is a schematic block diagram of an embodiment of a distributedcomputing system 10 that includes a user device 12 and/or a user device14, a distributed storage and/or task (DST) processing unit 16, adistributed storage and/or task network (DSTN) managing unit 18, a DSTintegrity processing unit 20, and a distributed storage and/or tasknetwork (DSTN) module 22. The components of the distributed computingsystem 10 are coupled via a network 24, which may include one or morewireless and/or wire lined communication systems; one or more privateintranet systems and/or public internet systems; and/or one or morelocal area networks (LAN) and/or wide area networks (WAN).

The DSTN module 22 includes a plurality of distributed storage and/ortask (DST) execution units 36 that may be located at geographicallydifferent sites (e.g., one in Chicago, one in Milwaukee, etc.). Each ofthe DST execution units is operable to store dispersed error encodeddata and/or to execute, in a distributed manner, one or more tasks ondata. The tasks may be a simple function (e.g., a mathematical function,a logic function, an identify function, a find function, a search enginefunction, a replace function, etc.), a complex function (e.g.,compression, human and/or computer language translation, text-to-voiceconversion, voice-to-text conversion, etc.), multiple simple and/orcomplex functions, one or more algorithms, one or more applications,etc.

Each of the user devices 12-14, the DST processing unit 16, the DSTNmanaging unit 18, and the DST integrity processing unit 20 include acomputing core 26 and may be a portable computing device and/or a fixedcomputing device. A portable computing device may be a social networkingdevice, a gaming device, a cell phone, a smart phone, a personal digitalassistant, a digital music player, a digital video player, a laptopcomputer, a handheld computer, a tablet, a video game controller, and/orany other portable device that includes a computing core. A fixedcomputing device may be a personal computer (PC), a computer server, acable set-top box, a satellite receiver, a television set, a printer, afax machine, home entertainment equipment, a video game console, and/orany type of home or office computing equipment. User device 12 and DSTprocessing unit 16 are configured to include a DST client module 34.

With respect to interfaces, each interface 30, 32, and 33 includessoftware and/or hardware to support one or more communication links viathe network 24 indirectly and/or directly. For example, interfaces 30support a communication link (e.g., wired, wireless, direct, via a LAN,via the network 24, etc.) between user device 14 and the DST processingunit 16. As another example, interface 32 supports communication links(e.g., a wired connection, a wireless connection, a LAN connection,and/or any other type of connection to/from the network 24) between userdevice 12 and the DSTN module 22 and between the DST processing unit 16and the DSTN module 22. As yet another example, interface 33 supports acommunication link for each of the DSTN managing unit 18 and DSTintegrity processing unit 20 to the network 24.

The distributed computing system 10 is operable to support dispersedstorage (DS) error encoded data storage and retrieval, to supportdistributed task processing on received data, and/or to supportdistributed task processing on stored data. In general and with respectto DS error encoded data storage and retrieval, the distributedcomputing system 10 supports three primary operations: storagemanagement, data storage and retrieval (an example of which will bediscussed with reference to FIGS. 20-26), and data storage integrityverification. In accordance with these three primary functions, data canbe encoded, distributedly stored in physically different locations, andsubsequently retrieved in a reliable and secure manner. Such a system istolerant of a significant number of failures (e.g., up to a failurelevel, which may be greater than or equal to a pillar width minus adecode threshold minus one) that may result from individual storagedevice failures and/or network equipment failures without loss of dataand without the need for a redundant or backup copy. Further, the systemallows the data to be stored for an indefinite period of time withoutdata loss and does so in a secure manner (e.g., the system is veryresistant to attempts at hacking the data).

The second primary function (i.e., distributed data storage andretrieval) begins and ends with a user device 12-14. For instance, if asecond type of user device 14 has data 40 to store in the DSTN module22, it sends the data 40 to the DST processing unit 16 via its interface30. The interface 30 functions to mimic a conventional operating system(OS) file system interface (e.g., network file system (NFS), flash filesystem (FFS), disk file system (DFS), file transfer protocol (FTP),web-based distributed authoring and versioning (WebDAV), etc.) and/or ablock memory interface (e.g., small computer system interface (SCSI),internet small computer system interface (iSCSI), etc.). In addition,the interface 30 may attach a user identification code (ID) to the data40.

To support storage management, the DSTN managing unit 18 performs DSmanagement services. One such DS management service includes the DSTNmanaging unit 18 establishing distributed data storage parameters (e.g.,vault creation, distributed storage parameters, security parameters,billing information, user profile information, etc.) for a user device12-14 individually or as part of a group of user devices. For example,the DSTN managing unit 18 coordinates creation of a vault (e.g., avirtual memory block) within memory of the DSTN module 22 for a userdevice, a group of devices, or for public access and establishes pervault dispersed storage (DS) error encoding parameters for a vault. TheDSTN managing unit 18 may facilitate storage of DS error encodingparameters for each vault of a plurality of vaults by updating registryinformation for the distributed computing system 10. The facilitatingincludes storing updated registry information in one or more of the DSTNmodule 22, the user device 12, the DST processing unit 16, and the DSTintegrity processing unit 20.

The DS error encoding parameters (e.g., or dispersed storage errorcoding parameters) include data segmenting information (e.g., how manysegments data (e.g., a file, a group of files, a data block, etc.) isdivided into), segment security information (e.g., per segmentencryption, compression, integrity checksum, etc.), error codinginformation (e.g., pillar width, decode threshold, read threshold, writethreshold, etc.), slicing information (e.g., the number of encoded dataslices that will be created for each data segment); and slice securityinformation (e.g., per encoded data slice encryption, compression,integrity checksum, etc.).

The DSTN managing unit 18 creates and stores user profile information(e.g., an access control list (ACL)) in local memory and/or withinmemory of the DSTN module 22. The user profile information includesauthentication information, permissions, and/or the security parameters.The security parameters may include encryption/decryption scheme, one ormore encryption keys, key generation scheme, and/or dataencoding/decoding scheme.

The DSTN managing unit 18 creates billing information for a particularuser, a user group, a vault access, public vault access, etc. Forinstance, the DSTN managing unit 18 tracks the number of times a useraccesses a private vault and/or public vaults, which can be used togenerate a per-access billing information. In another instance, the DSTNmanaging unit 18 tracks the amount of data stored and/or retrieved by auser device and/or a user group, which can be used to generate aper-data-amount billing information.

Another DS management service includes the DSTN managing unit 18performing network operations, network administration, and/or networkmaintenance. Network operations includes authenticating user dataallocation requests (e.g., read and/or write requests), managingcreation of vaults, establishing authentication credentials for userdevices, adding/deleting components (e.g., user devices, DST executionunits, and/or DST processing units) from the distributed computingsystem 10, and/or establishing authentication credentials for DSTexecution units 36. Network administration includes monitoring devicesand/or units for failures, maintaining vault information, determiningdevice and/or unit activation status, determining device and/or unitloading, and/or determining any other system level operation thataffects the performance level of the system 10. Network maintenanceincludes facilitating replacing, upgrading, repairing, and/or expandinga device and/or unit of the system 10.

To support data storage integrity verification within the distributedcomputing system 10, the DST integrity processing unit 20 performsrebuilding of ‘bad’ or missing encoded data slices. At a high level, theDST integrity processing unit 20 performs rebuilding by periodicallyattempting to retrieve/list encoded data slices, and/or slice names ofthe encoded data slices, from the DSTN module 22. For retrieved encodedslices, they are checked for errors due to data corruption, outdatedversion, etc. If a slice includes an error, it is flagged as a ‘bad’slice. For encoded data slices that were not received and/or not listed,they are flagged as missing slices. Bad and/or missing slices aresubsequently rebuilt using other retrieved encoded data slices that aredeemed to be good slices to produce rebuilt slices. The rebuilt slicesare stored in memory of the DSTN module 22. Note that the DST integrityprocessing unit 20 may be a separate unit as shown, it may be includedin the DSTN module 22, it may be included in the DST processing unit 16,and/or distributed among the DST execution units 36.

To support distributed task processing on received data, the distributedcomputing system 10 has two primary operations: DST (distributed storageand/or task processing) management and DST execution on received data(an example of which will be discussed with reference to FIGS. 3-19).With respect to the storage portion of the DST management, the DSTNmanaging unit 18 functions as previously described. With respect to thetasking processing of the DST management, the DSTN managing unit 18performs distributed task processing (DTP) management services. One suchDTP management service includes the DSTN managing unit 18 establishingDTP parameters (e.g., user-vault affiliation information, billinginformation, user-task information, etc.) for a user device 12-14individually or as part of a group of user devices.

Another DTP management service includes the DSTN managing unit 18performing DTP network operations, network administration (which isessentially the same as described above), and/or network maintenance(which is essentially the same as described above). Network operationsinclude, but are not limited to, authenticating user task processingrequests (e.g., valid request, valid user, etc.), authenticating resultsand/or partial results, establishing DTP authentication credentials foruser devices, adding/deleting components (e.g., user devices, DSTexecution units, and/or DST processing units) from the distributedcomputing system, and/or establishing DTP authentication credentials forDST execution units.

To support distributed task processing on stored data, the distributedcomputing system 10 has two primary operations: DST (distributed storageand/or task) management and DST execution on stored data. With respectto the DST execution on stored data, if the second type of user device14 has a task request 38 for execution by the DSTN module 22, it sendsthe task request 38 to the DST processing unit 16 via its interface 30.An example of DST execution on stored data will be discussed in greaterdetail with reference to FIGS. 27-39. With respect to the DSTmanagement, it is substantially similar to the DST management to supportdistributed task processing on received data.

FIG. 2 is a schematic block diagram of an embodiment of a computing core26 that includes a processing module 50, a memory controller 52, mainmemory 54, a video graphics processing unit 55, an input/output (TO)controller 56, a peripheral component interconnect (PCI) interface 58,an IO interface module 60, at least one IO device interface module 62, aread only memory (ROM) basic input output system (BIOS) 64, and one ormore memory interface modules. The one or more memory interfacemodule(s) includes one or more of a universal serial bus (USB) interfacemodule 66, a host bus adapter (HBA) interface module 68, a networkinterface module 70, a flash interface module 72, a hard drive interfacemodule 74, and a DSTN interface module 76.

The DSTN interface module 76 functions to mimic a conventional operatingsystem (OS) file system interface (e.g., network file system (NFS),flash file system (FFS), disk file system (DFS), file transfer protocol(FTP), web-based distributed authoring and versioning (WebDAV), etc.)and/or a block memory interface (e.g., small computer system interface(SCSI), internet small computer system interface (iSCSI), etc.). TheDSTN interface module 76 and/or the network interface module 70 mayfunction as the interface 30 of the user device 14 of FIG. 1. Furthernote that the IO device interface module 62 and/or the memory interfacemodules may be collectively or individually referred to as IO ports.

FIG. 3 is a diagram of an example of the distributed computing systemperforming a distributed storage and task processing operation. Thedistributed computing system includes a DST (distributed storage and/ortask) client module 34 (which may be in user device 14 and/or in DSTprocessing unit 16 of FIG. 1), a network 24, a plurality of DSTexecution units 1-n that includes two or more DST execution units 36 ofFIG. 1 (which form at least a portion of DSTN module 22 of FIG. 1), aDST managing module (not shown), and a DST integrity verification module(not shown). The DST client module 34 includes an outbound DSTprocessing section 80 and an inbound DST processing section 82. Each ofthe DST execution units 1-n includes a controller 86, a processingmodule 84, memory 88, a DT (distributed task) execution module 90, and aDST client module 34.

In an example of operation, the DST client module 34 receives data 92and one or more tasks 94 to be performed upon the data 92. The data 92may be of any size and of any content, where, due to the size (e.g.,greater than a few Terabytes), the content (e.g., secure data, etc.),and/or task(s) (e.g., MIPS intensive), distributed processing of thetask(s) on the data is desired. For example, the data 92 may be one ormore digital books, a copy of a company's emails, a large-scale Internetsearch, a video security file, one or more entertainment video files(e.g., television programs, movies, etc.), data files, and/or any otherlarge amount of data (e.g., greater than a few Terabytes).

Within the DST client module 34, the outbound DST processing section 80receives the data 92 and the task(s) 94. The outbound DST processingsection 80 processes the data 92 to produce slice groupings 96. As anexample of such processing, the outbound DST processing section 80partitions the data 92 into a plurality of data partitions. For eachdata partition, the outbound DST processing section 80 dispersed storage(DS) error encodes the data partition to produce encoded data slices andgroups the encoded data slices into a slice grouping 96. In addition,the outbound DST processing section 80 partitions the task 94 intopartial tasks 98, where the number of partial tasks 98 may correspond tothe number of slice groupings 96.

The outbound DST processing section 80 then sends, via the network 24,the slice groupings 96 and the partial tasks 98 to the DST executionunits 1-n of the DSTN module 22 of FIG. 1. For example, the outbound DSTprocessing section 80 sends slice group 1 and partial task 1 to DSTexecution unit 1. As another example, the outbound DST processingsection 80 sends slice group #n and partial task #n to DST executionunit #n.

Each DST execution unit performs its partial task 98 upon its slicegroup 96 to produce partial results 102. For example, DST execution unit#1 performs partial task #1 on slice group #1 to produce a partialresult #1, for results. As a more specific example, slice group #1corresponds to a data partition of a series of digital books and thepartial task #1 corresponds to searching for specific phrases, recordingwhere the phrase is found, and establishing a phrase count. In this morespecific example, the partial result #1 includes information as to wherethe phrase was found and includes the phrase count.

Upon completion of generating their respective partial results 102, theDST execution units send, via the network 24, their partial results 102to the inbound DST processing section 82 of the DST client module 34.The inbound DST processing section 82 processes the received partialresults 102 to produce a result 104. Continuing with the specificexample of the preceding paragraph, the inbound DST processing section82 combines the phrase count from each of the DST execution units 36 toproduce a total phrase count. In addition, the inbound DST processingsection 82 combines the ‘where the phrase was found’ information fromeach of the DST execution units 36 within their respective datapartitions to produce ‘where the phrase was found’ information for theseries of digital books.

In another example of operation, the DST client module 34 requestsretrieval of stored data within the memory of the DST execution units 36(e.g., memory of the DSTN module). In this example, the task 94 isretrieve data stored in the memory of the DSTN module. Accordingly, theoutbound DST processing section 80 converts the task 94 into a pluralityof partial tasks 98 and sends the partial tasks 98 to the respective DSTexecution units 1-n.

In response to the partial task 98 of retrieving stored data, a DSTexecution unit 36 identifies the corresponding encoded data slices 100and retrieves them. For example, DST execution unit #1 receives partialtask #1 and retrieves, in response thereto, retrieved slices #1. The DSTexecution units 36 send their respective retrieved slices 100 to theinbound DST processing section 82 via the network 24.

The inbound DST processing section 82 converts the retrieved slices 100into data 92. For example, the inbound DST processing section 82de-groups the retrieved slices 100 to produce encoded slices per datapartition. The inbound DST processing section 82 then DS error decodesthe encoded slices per data partition to produce data partitions. Theinbound DST processing section 82 de-partitions the data partitions torecapture the data 92.

FIG. 4 is a schematic block diagram of an embodiment of an outbounddistributed storage and/or task (DST) processing section 80 of a DSTclient module 34 FIG. 1 coupled to a DSTN module 22 of a FIG. 1 (e.g., aplurality of n DST execution units 36) via a network 24. The outboundDST processing section 80 includes a data partitioning module 110, adispersed storage (DS) error encoding module 112, a grouping selectormodule 114, a control module 116, and a distributed task control module118.

In an example of operation, the data partitioning module 110 partitionsdata 92 into a plurality of data partitions 120. The number ofpartitions and the size of the partitions may be selected by the controlmodule 116 via control 160 based on the data 92 (e.g., its size, itscontent, etc.), a corresponding task 94 to be performed (e.g., simple,complex, single step, multiple steps, etc.), DS encoding parameters(e.g., pillar width, decode threshold, write threshold, segment securityparameters, slice security parameters, etc.), capabilities of the DSTexecution units 36 (e.g., processing resources, availability ofprocessing recourses, etc.), and/or as may be inputted by a user, systemadministrator, or other operator (human or automated). For example, thedata partitioning module 110 partitions the data 92 (e.g., 100Terabytes) into 100,000 data segments, each being 1 Gigabyte in size.Alternatively, the data partitioning module 110 partitions the data 92into a plurality of data segments, where some of data segments are of adifferent size, are of the same size, or a combination thereof.

The DS error encoding module 112 receives the data partitions 120 in aserial manner, a parallel manner, and/or a combination thereof. For eachdata partition 120, the DS error encoding module 112 DS error encodesthe data partition 120 in accordance with control information 160 fromthe control module 116 to produce encoded data slices 122. The DS errorencoding includes segmenting the data partition into data segments,segment security processing (e.g., encryption, compression,watermarking, integrity check (e.g., CRC), etc.), error encoding,slicing, and/or per slice security processing (e.g., encryption,compression, watermarking, integrity check (e.g., CRC), etc.). Thecontrol information 160 indicates which steps of the DS error encodingare active for a given data partition and, for active steps, indicatesthe parameters for the step. For example, the control information 160indicates that the error encoding is active and includes error encodingparameters (e.g., pillar width, decode threshold, write threshold, readthreshold, type of error encoding, etc.).

The grouping selector module 114 groups the encoded slices 122 of a datapartition into a set of slice groupings 96. The number of slicegroupings corresponds to the number of DST execution units 36 identifiedfor a particular task 94. For example, if five DST execution units 36are identified for the particular task 94, the group selecting modulegroups the encoded slices 122 of a data partition into five slicegroupings 96. The grouping selector module 114 outputs the slicegroupings 96 to the corresponding DST execution units 36 via the network24.

The distributed task control module 118 receives the task 94 andconverts the task 94 into a set of partial tasks 98. For example, thedistributed task control module 118 receives a task to find where in thedata (e.g., a series of books) a phrase occurs and a total count of thephrase usage in the data. In this example, the distributed task controlmodule 118 replicates the task 94 for each DST execution unit 36 toproduce the partial tasks 98. In another example, the distributed taskcontrol module 118 receives a task to find where in the data a firstphrase occurs, where in the data a second phrase occurs, and a totalcount for each phrase usage in the data. In this example, thedistributed task control module 118 generates a first set of partialtasks 98 for finding and counting the first phase and a second set ofpartial tasks for finding and counting the second phrase. Thedistributed task control module 118 sends respective first and/or secondpartial tasks 98 to each DST execution unit 36.

FIG. 5 is a logic diagram of an example of a method for outbounddistributed storage and task (DST) processing that begins at step 126where a DST client module receives data and one or more correspondingtasks. The method continues at step 128 where the DST client moduledetermines a number of DST units to support the task for one or moredata partitions. For example, the DST client module may determine thenumber of DST units to support the task based on the size of the data,the requested task, the content of the data, a predetermined number(e.g., user indicated, system administrator determined, etc.), availableDST units, capability of the DST units, and/or any other factorregarding distributed task processing of the data. The DST client modulemay select the same DST units for each data partition, may selectdifferent DST units for the data partitions, or a combination thereof.

The method continues at step 130 where the DST client module determinesprocessing parameters of the data based on the number of DST unitsselected for distributed task processing. The processing parametersinclude data partitioning information, DS encoding parameters, and/orslice grouping information. The data partitioning information includes anumber of data partitions, size of each data partition, and/ororganization of the data partitions (e.g., number of data blocks in apartition, the size of the data blocks, and arrangement of the datablocks). The DS encoding parameters include segmenting information,segment security information, error encoding information (e.g.,dispersed storage error encoding function parameters including one ormore of pillar width, decode threshold, write threshold, read threshold,generator matrix), slicing information, and/or per slice securityinformation. The slice grouping information includes informationregarding how to arrange the encoded data slices into groups for theselected DST units. As a specific example, if the DST client moduledetermines that five DST units are needed to support the task, then itdetermines that the error encoding parameters include a pillar width offive and a decode threshold of three.

The method continues at step 132 where the DST client module determinestask partitioning information (e.g., how to partition the tasks) basedon the selected DST units and data processing parameters. The dataprocessing parameters include the processing parameters and DST unitcapability information. The DST unit capability information includes thenumber of DT (distributed task) execution units, execution capabilitiesof each DT execution unit (e.g., MIPS capabilities, processing resources(e.g., quantity and capability of microprocessors, CPUs, digital signalprocessors, co-processor, microcontrollers, arithmetic logic circuitry,and/or and the other analog and/or digital processing circuitry),availability of the processing resources, memory information (e.g.,type, size, availability, etc.)), and/or any information germane toexecuting one or more tasks.

The method continues at step 134 where the DST client module processesthe data in accordance with the processing parameters to produce slicegroupings. The method continues at step 136 where the DST client modulepartitions the task based on the task partitioning information toproduce a set of partial tasks. The method continues at step 138 wherethe DST client module sends the slice groupings and the correspondingpartial tasks to respective DST units.

FIG. 6 is a schematic block diagram of an embodiment of the dispersedstorage (DS) error encoding module 112 of an outbound distributedstorage and task (DST) processing section. The DS error encoding module112 includes a segment processing module 142, a segment securityprocessing module 144, an error encoding module 146, a slicing module148, and a per slice security processing module 150. Each of thesemodules is coupled to a control module 116 to receive controlinformation 160 therefrom.

In an example of operation, the segment processing module 142 receives adata partition 120 from a data partitioning module and receivessegmenting information as the control information 160 from the controlmodule 116. The segmenting information indicates how the segmentprocessing module 142 is to segment the data partition 120. For example,the segmenting information indicates how many rows to segment the databased on a decode threshold of an error encoding scheme, indicates howmany columns to segment the data into based on a number and size of datablocks within the data partition 120, and indicates how many columns toinclude in a data segment 152. The segment processing module 142segments the data 120 into data segments 152 in accordance with thesegmenting information.

The segment security processing module 144, when enabled by the controlmodule 116, secures the data segments 152 based on segment securityinformation received as control information 160 from the control module116. The segment security information includes data compression,encryption, watermarking, integrity check (e.g., cyclic redundancy check(CRC), etc.), and/or any other type of digital security. For example,when the segment security processing module 144 is enabled, it maycompress a data segment 152, encrypt the compressed data segment, andgenerate a CRC value for the encrypted data segment to produce a securedata segment 154. When the segment security processing module 144 is notenabled, it passes the data segments 152 to the error encoding module146 or is bypassed such that the data segments 152 are provided to theerror encoding module 146.

The error encoding module 146 encodes the secure data segments 154 inaccordance with error correction encoding parameters received as controlinformation 160 from the control module 116. The error correctionencoding parameters (e.g., also referred to as dispersed storage errorcoding parameters) include identifying an error correction encodingscheme (e.g., forward error correction algorithm, a Reed-Solomon basedalgorithm, an online coding algorithm, an information dispersalalgorithm, etc.), a pillar width, a decode threshold, a read threshold,a write threshold, etc. For example, the error correction encodingparameters identify a specific error correction encoding scheme,specifies a pillar width of five, and specifies a decode threshold ofthree. From these parameters, the error encoding module 146 encodes adata segment 154 to produce an encoded data segment 156.

The slicing module 148 slices the encoded data segment 156 in accordancewith the pillar width of the error correction encoding parametersreceived as control information 160. For example, if the pillar width isfive, the slicing module 148 slices an encoded data segment 156 into aset of five encoded data slices. As such, for a plurality of encodeddata segments 156 for a given data partition, the slicing module outputsa plurality of sets of encoded data slices 158.

The per slice security processing module 150, when enabled by thecontrol module 116, secures each encoded data slice 158 based on slicesecurity information received as control information 160 from thecontrol module 116. The slice security information includes datacompression, encryption, watermarking, integrity check (e.g., CRC,etc.), and/or any other type of digital security. For example, when theper slice security processing module 150 is enabled, it compresses anencoded data slice 158, encrypts the compressed encoded data slice, andgenerates a CRC value for the encrypted encoded data slice to produce asecure encoded data slice 122. When the per slice security processingmodule 150 is not enabled, it passes the encoded data slices 158 or isbypassed such that the encoded data slices 158 are the output of the DSerror encoding module 112. Note that the control module 116 may beomitted and each module stores its own parameters.

FIG. 7 is a diagram of an example of a segment processing of a dispersedstorage (DS) error encoding module. In this example, a segmentprocessing module 142 receives a data partition 120 that includes 45data blocks (e.g., d1-d45), receives segmenting information (i.e.,control information 160) from a control module, and segments the datapartition 120 in accordance with the control information 160 to producedata segments 152. Each data block may be of the same size as other datablocks or of a different size. In addition, the size of each data blockmay be a few bytes to megabytes of data. As previously mentioned, thesegmenting information indicates how many rows to segment the datapartition into, indicates how many columns to segment the data partitioninto, and indicates how many columns to include in a data segment.

In this example, the decode threshold of the error encoding scheme isthree; as such the number of rows to divide the data partition into isthree. The number of columns for each row is set to 15, which is basedon the number and size of data blocks. The data blocks of the datapartition are arranged in rows and columns in a sequential order (i.e.,the first row includes the first 15 data blocks; the second row includesthe second 15 data blocks; and the third row includes the last 15 datablocks).

With the data blocks arranged into the desired sequential order, theyare divided into data segments based on the segmenting information. Inthis example, the data partition is divided into 8 data segments; thefirst 7 include 2 columns of three rows and the last includes 1 columnof three rows. Note that the first row of the 8 data segments is insequential order of the first 15 data blocks; the second row of the 8data segments in sequential order of the second 15 data blocks; and thethird row of the 8 data segments in sequential order of the last 15 datablocks. Note that the number of data blocks, the grouping of the datablocks into segments, and size of the data blocks may vary toaccommodate the desired distributed task processing function.

FIG. 8 is a diagram of an example of error encoding and slicingprocessing of the dispersed error encoding processing the data segmentsof FIG. 7. In this example, data segment 1 includes 3 rows with each rowbeing treated as one word for encoding. As such, data segment 1 includesthree words for encoding: word 1 including data blocks d1 and d2, word 2including data blocks d16 and d17, and word 3 including data blocks d31and d32. Each of data segments 2-7 includes three words where each wordincludes two data blocks. Data segment 8 includes three words where eachword includes a single data block (e.g., d15, d30, and d45).

In operation, an error encoding module 146 and a slicing module 148convert each data segment into a set of encoded data slices inaccordance with error correction encoding parameters as controlinformation 160. More specifically, when the error correction encodingparameters indicate a unity matrix Reed-Solomon based encodingalgorithm, 5 pillars, and decode threshold of 3, the first three encodeddata slices of the set of encoded data slices for a data segment aresubstantially similar to the corresponding word of the data segment. Forinstance, when the unity matrix Reed-Solomon based encoding algorithm isapplied to data segment 1, the content of the first encoded data slice(DS1 _(—) d 1&2) of the first set of encoded data slices (e.g.,corresponding to data segment 1) is substantially similar to content ofthe first word (e.g., d1 & d2); the content of the second encoded dataslice (DS1 _(—) d 16&17) of the first set of encoded data slices issubstantially similar to content of the second word (e.g., d16 & d17);and the content of the third encoded data slice (DS1 _(—) d 31&32) ofthe first set of encoded data slices is substantially similar to contentof the third word (e.g., d31 & d32).

The content of the fourth and fifth encoded data slices (e.g., ES1_1 andES1_2) of the first set of encoded data slices include error correctiondata based on the first-third words of the first data segment. With suchan encoding and slicing scheme, retrieving any three of the five encodeddata slices allows the data segment to be accurately reconstructed.

The encoding and slices of data segments 2-7 yield sets of encoded dataslices similar to the set of encoded data slices of data segment 1. Forinstance, the content of the first encoded data slice (DS2 _(—) d 3&4)of the second set of encoded data slices (e.g., corresponding to datasegment 2) is substantially similar to content of the first word (e.g.,d3 & d4); the content of the second encoded data slice (DS2 _(—) d18&19) of the second set of encoded data slices is substantially similarto content of the second word (e.g., d18 & d19); and the content of thethird encoded data slice (DS2 _(—) d 33&34) of the second set of encodeddata slices is substantially similar to content of the third word (e.g.,d33 & d34). The content of the fourth and fifth encoded data slices(e.g., ES1_1 and ES1_2) of the second set of encoded data slicesincludes error correction data based on the first-third words of thesecond data segment.

FIG. 9 is a diagram of an example of grouping selection processing of anoutbound distributed storage and task (DST) processing in accordancewith group selection information as control information 160 from acontrol module. Encoded slices for data partition 122 are grouped inaccordance with the control information 160 to produce slice groupings96. In this example, a grouping selection module 114 organizes theencoded data slices into five slice groupings (e.g., one for each DSTexecution unit of a distributed storage and task network (DSTN) module).As a specific example, the grouping selection module 114 creates a firstslice grouping for a DST execution unit #1, which includes first encodedslices of each of the sets of encoded slices. As such, the first DSTexecution unit receives encoded data slices corresponding to data blocks1-15 (e.g., encoded data slices of contiguous data).

The grouping selection module 114 also creates a second slice groupingfor a DST execution unit #2, which includes second encoded slices ofeach of the sets of encoded slices. As such, the second DST executionunit receives encoded data slices corresponding to data blocks 16-30.The grouping selection module 114 further creates a third slice groupingfor DST execution unit #3, which includes third encoded slices of eachof the sets of encoded slices. As such, the third DST execution unitreceives encoded data slices corresponding to data blocks 31-45.

The grouping selection module 114 creates a fourth slice grouping forDST execution unit #4, which includes fourth encoded slices of each ofthe sets of encoded slices. As such, the fourth DST execution unitreceives encoded data slices corresponding to first error encodinginformation (e.g., encoded data slices of error coding (EC) data). Thegrouping selection module 114 further creates a fifth slice grouping forDST execution unit #5, which includes fifth encoded slices of each ofthe sets of encoded slices. As such, the fifth DST execution unitreceives encoded data slices corresponding to second error encodinginformation.

FIG. 10 is a diagram of an example of converting data 92 into slicegroups that expands on the preceding figures. As shown, the data 92 ispartitioned in accordance with a partitioning function 164 into aplurality of data partitions (1−x, where x is an integer greater than4). Each data partition (or chunkset of data) is encoded and groupedinto slice groupings as previously discussed by an encoding and groupingfunction 166. For a given data partition, the slice groupings are sentto distributed storage and task (DST) execution units. From datapartition to data partition, the ordering of the slice groupings to theDST execution units may vary.

For example, the slice groupings of data partition #1 is sent to the DSTexecution units such that the first DST execution receives first encodeddata slices of each of the sets of encoded data slices, whichcorresponds to a first continuous data chunk of the first data partition(e.g., refer to FIG. 9), a second DST execution receives second encodeddata slices of each of the sets of encoded data slices, whichcorresponds to a second continuous data chunk of the first datapartition, etc.

For the second data partition, the slice groupings may be sent to theDST execution units in a different order than it was done for the firstdata partition. For instance, the first slice grouping of the seconddata partition (e.g., slice group 2_1) is sent to the second DSTexecution unit; the second slice grouping of the second data partition(e.g., slice group 2_2) is sent to the third DST execution unit; thethird slice grouping of the second data partition (e.g., slice group2_3) is sent to the fourth DST execution unit; the fourth slice groupingof the second data partition (e.g., slice group 2_4, which includesfirst error coding information) is sent to the fifth

DST execution unit; and the fifth slice grouping of the second datapartition (e.g., slice group 2_5, which includes second error codinginformation) is sent to the first DST execution unit.

The pattern of sending the slice groupings to the set of DST executionunits may vary in a predicted pattern, a random pattern, and/or acombination thereof from data partition to data partition. In addition,from data partition to data partition, the set of DST execution unitsmay change. For example, for the first data partition, DST executionunits 1-5 may be used; for the second data partition, DST executionunits 6-10 may be used; for the third data partition, DST executionunits 3-7 may be used; etc. As is also shown, the task is divided intopartial tasks that are sent to the DST execution units in conjunctionwith the slice groupings of the data partitions.

FIG. 11 is a schematic block diagram of an embodiment of a DST(distributed storage and/or task) execution unit that includes aninterface 169, a controller 86, memory 88, one or more DT (distributedtask) execution modules 90, and a DST client module 34. The memory 88 isof sufficient size to store a significant number of encoded data slices(e.g., thousands of slices to hundreds-of-millions of slices) and mayinclude one or more hard drives and/or one or more solid-state memorydevices (e.g., flash memory, DRAM, etc.).

In an example of storing a slice group, the DST execution modulereceives a slice grouping 96 (e.g., slice group #1) via interface 169.The slice grouping 96 includes, per partition, encoded data slices ofcontiguous data or encoded data slices of error coding (EC) data. Forslice group #1, the DST execution module receives encoded data slices ofcontiguous data for partitions #1 and #x (and potentially others between3 and x) and receives encoded data slices of EC data for partitions #2and #3 (and potentially others between 3 and x). Examples of encodeddata slices of contiguous data and encoded data slices of error coding(EC) data are discussed with reference to FIG. 9. The memory 88 storesthe encoded data slices of slice groupings 96 in accordance with memorycontrol information 174 it receives from the controller 86.

The controller 86 (e.g., a processing module, a CPU, etc.) generates thememory control information 174 based on a partial task(s) 98 anddistributed computing information (e.g., user information (e.g., userID, distributed computing permissions, data access permission, etc.),vault information (e.g., virtual memory assigned to user, user group,temporary storage for task processing, etc.), task validationinformation, etc.). For example, the controller 86 interprets thepartial task(s) 98 in light of the distributed computing information todetermine whether a requestor is authorized to perform the task 98, isauthorized to access the data, and/or is authorized to perform the taskon this particular data. When the requestor is authorized, thecontroller 86 determines, based on the task 98 and/or another input,whether the encoded data slices of the slice grouping 96 are to betemporarily stored or permanently stored. Based on the foregoing, thecontroller 86 generates the memory control information 174 to write theencoded data slices of the slice grouping 96 into the memory 88 and toindicate whether the slice grouping 96 is permanently stored ortemporarily stored.

With the slice grouping 96 stored in the memory 88, the controller 86facilitates execution of the partial task(s) 98. In an example, thecontroller 86 interprets the partial task 98 in light of thecapabilities of the DT execution module(s) 90. The capabilities includeone or more of MIPS capabilities, processing resources (e.g., quantityand capability of microprocessors, CPUs, digital signal processors,co-processor, microcontrollers, arithmetic logic circuitry, and/or anyother analog and/or digital processing circuitry), availability of theprocessing resources, etc. If the controller 86 determines that the DTexecution module(s) 90 have sufficient capabilities, it generates taskcontrol information 176.

The task control information 176 may be a generic instruction (e.g.,perform the task on the stored slice grouping) or a series ofoperational codes. In the former instance, the DT execution module 90includes a co-processor function specifically configured (fixed orprogrammed) to perform the desired task 98. In the latter instance, theDT execution module 90 includes a general processor topology where thecontroller stores an algorithm corresponding to the particular task 98.In this instance, the controller 86 provides the operational codes(e.g., assembly language, source code of a programming language, objectcode, etc.) of the algorithm to the DT execution module 90 forexecution.

Depending on the nature of the task 98, the DT execution module 90 maygenerate intermediate partial results 102 that are stored in the memory88 or in a cache memory (not shown) within the DT execution module 90.In either case, when the DT execution module 90 completes execution ofthe partial task 98, it outputs one or more partial results 102. Thepartial results 102 may also be stored in memory 88.

If, when the controller 86 is interpreting whether capabilities of theDT execution module(s) 90 can support the partial task 98, thecontroller 86 determines that the DT execution module(s) 90 cannotadequately support the task 98 (e.g., does not have the right resources,does not have sufficient available resources, available resources wouldbe too slow, etc.), it then determines whether the partial task 98should be fully offloaded or partially offloaded.

If the controller 86 determines that the partial task 98 should be fullyoffloaded, it generates DST control information 178 and provides it tothe DST client module 34. The DST control information 178 includes thepartial task 98, memory storage information regarding the slice grouping96, and distribution instructions. The distribution instructionsinstruct the DST client module 34 to divide the partial task 98 intosub-partial tasks 172, to divide the slice grouping 96 into sub-slicegroupings 170, and identify other DST execution units. The DST clientmodule 34 functions in a similar manner as the DST client module 34 ofFIGS. 3-10 to produce the sub-partial tasks 172 and the sub-slicegroupings 170 in accordance with the distribution instructions.

The DST client module 34 receives DST feedback 168 (e.g., sub-partialresults), via the interface 169, from the DST execution units to whichthe task was offloaded. The DST client module 34 provides thesub-partial results to the DST execution unit, which processes thesub-partial results to produce the partial result(s) 102.

If the controller 86 determines that the partial task 98 should bepartially offloaded, it determines what portion of the task 98 and/orslice grouping 96 should be processed locally and what should beoffloaded. For the portion that is being locally processed, thecontroller 86 generates task control information 176 as previouslydiscussed. For the portion that is being offloaded, the controller 86generates DST control information 178 as previously discussed.

When the DST client module 34 receives DST feedback 168 (e.g.,sub-partial results) from the DST executions units to which a portion ofthe task was offloaded, it provides the sub-partial results to the DTexecution module 90. The DT execution module 90 processes thesub-partial results with the sub-partial results it created to producethe partial result(s) 102.

The memory 88 may be further utilized to retrieve one or more of storedslices 100, stored results 104, partial results 102 when the DTexecution module 90 stores partial results 102 and/or results 104 andthe memory 88. For example, when the partial task 98 includes aretrieval request, the controller 86 outputs the memory control 174 tothe memory 88 to facilitate retrieval of slices 100 and/or results 104.

FIG. 12 is a schematic block diagram of an example of operation of adistributed storage and task (DST) execution unit storing encoded dataslices and executing a task thereon. To store the encoded data slices ofa partition 1 of slice grouping 1, a controller 86 generates writecommands as memory control information 174 such that the encoded slicesare stored in desired locations (e.g., permanent or temporary) withinmemory 88.

Once the encoded slices are stored, the controller 86 provides taskcontrol information 176 to a distributed task (DT) execution module 90.As a first step of executing the task in accordance with the taskcontrol information 176, the DT execution module 90 retrieves theencoded slices from memory 88. The DT execution module 90 thenreconstructs contiguous data blocks of a data partition. As shown forthis example, reconstructed contiguous data blocks of data partition 1include data blocks 1-15 (e.g., d1-d15).

With the contiguous data blocks reconstructed, the DT execution module90 performs the task on the reconstructed contiguous data blocks. Forexample, the task may be to search the reconstructed contiguous datablocks for a particular word or phrase, identify where in thereconstructed contiguous data blocks the particular word or phraseoccurred, and/or count the occurrences of the particular word or phraseon the reconstructed contiguous data blocks. The DST execution unitcontinues in a similar manner for the encoded data slices of otherpartitions in slice grouping 1. Note that with using the unity matrixerror encoding scheme previously discussed, if the encoded data slicesof contiguous data are uncorrupted, the decoding of them is a relativelystraightforward process of extracting the data.

If, however, an encoded data slice of contiguous data is corrupted (ormissing), it can be rebuilt by accessing other DST execution units thatare storing the other encoded data slices of the set of encoded dataslices of the corrupted encoded data slice. In this instance, the DSTexecution unit having the corrupted encoded data slices retrieves atleast three encoded data slices (of contiguous data and of error codingdata) in the set from the other DST execution units (recall for thisexample, the pillar width is 5 and the decode threshold is 3). The DSTexecution unit decodes the retrieved data slices using the DS errorencoding parameters to recapture the corresponding data segment. The DSTexecution unit then re-encodes the data segment using the DS errorencoding parameters to rebuild the corrupted encoded data slice. Oncethe encoded data slice is rebuilt, the DST execution unit functions aspreviously described.

FIG. 13 is a schematic block diagram of an embodiment of an inbounddistributed storage and/or task (DST) processing section 82 of a DSTclient module coupled to DST execution units of a distributed storageand task network (DSTN) module via a network 24. The inbound DSTprocessing section 82 includes a de-grouping module 180, a DS (dispersedstorage) error decoding module 182, a data de-partitioning module 184, acontrol module 186, and a distributed task control module 188. Note thatthe control module 186 and/or the distributed task control module 188may be separate modules from corresponding ones of outbound DSTprocessing section or may be the same modules.

In an example of operation, the DST execution units have completedexecution of corresponding partial tasks on the corresponding slicegroupings to produce partial results 102. The inbound DST processingsection 82 receives the partial results 102 via the distributed taskcontrol module 188. The inbound DST processing section 82 then processesthe partial results 102 to produce a final result, or results 104. Forexample, if the task was to find a specific word or phrase within data,the partial results 102 indicate where in each of the prescribedportions of the data the corresponding DST execution units found thespecific word or phrase. The distributed task control module 188combines the individual partial results 102 for the correspondingportions of the data into a final result 104 for the data as a whole.

In another example of operation, the inbound DST processing section 82is retrieving stored data from the DST execution units (i.e., the DSTNmodule). In this example, the DST execution units output encoded dataslices 100 corresponding to the data retrieval requests. The de-groupingmodule 180 receives retrieved slices 100 and de-groups them to produceencoded data slices per data partition 122. The DS error decoding module182 decodes, in accordance with DS error encoding parameters, theencoded data slices per data partition 122 to produce data partitions120.

The data de-partitioning module 184 combines the data partitions 120into the data 92. The control module 186 controls the conversion ofretrieve slices 100 into the data 92 using control signals 190 to eachof the modules. For instance, the control module 186 providesde-grouping information to the de-grouping module 180, provides the DSerror encoding parameters to the DS error decoding module 182, andprovides de-partitioning information to the data de-partitioning module184.

FIG. 14 is a logic diagram of an example of a method that is executableby distributed storage and task (DST) client module regarding inboundDST processing. The method begins at step 194 where the DST clientmodule receives partial results. The method continues at step 196 wherethe DST client module retrieves the task corresponding to the partialresults. For example, the partial results include header informationthat identifies the requesting entity, which correlates to the requestedtask.

The method continues at step 198 where the DST client module determinesresult processing information based on the task. For example, if thetask were to identify a particular word or phrase within the data, theresult processing information would indicate to aggregate the partialresults for the corresponding portions of the data to produce the finalresult. As another example, if the task were to count the occurrences ofa particular word or phrase within the data, results of processing theinformation would indicate to add the partial results to produce thefinal results. The method continues at step 200 where the DST clientmodule processes the partial results in accordance with the resultprocessing information to produce the final result or results.

FIG. 15 is a diagram of an example of de-grouping selection processingof an inbound distributed storage and task (DST) processing section of aDST client module. In general, this is an inverse process of thegrouping module of the outbound DST processing section of FIG. 9.Accordingly, for each data partition (e.g., partition #1), thede-grouping module retrieves the corresponding slice grouping from theDST execution units (EU) (e.g., DST 1-5).

As shown, DST execution unit #1 provides a first slice grouping, whichincludes the first encoded slices of each of the sets of encoded slices(e.g., encoded data slices of contiguous data of data blocks 1-15); DSTexecution unit #2 provides a second slice grouping, which includes thesecond encoded slices of each of the sets of encoded slices (e.g.,encoded data slices of contiguous data of data blocks 16-30); DSTexecution unit #3 provides a third slice grouping, which includes thethird encoded slices of each of the sets of encoded slices (e.g.,encoded data slices of contiguous data of data blocks 31-45); DSTexecution unit #4 provides a fourth slice grouping, which includes thefourth encoded slices of each of the sets of encoded slices (e.g., firstencoded data slices of error coding (EC) data); and DST execution unit#5 provides a fifth slice grouping, which includes the fifth encodedslices of each of the sets of encoded slices (e.g., first encoded dataslices of error coding (EC) data).

The de-grouping module de-groups the slice groupings (e.g., receivedslices 100) using a de-grouping selector 180 controlled by a controlsignal 190 as shown in the example to produce a plurality of sets ofencoded data slices (e.g., retrieved slices for a partition into sets ofslices 122). Each set corresponding to a data segment of the datapartition.

FIG. 16 is a schematic block diagram of an embodiment of a dispersedstorage (DS) error decoding module 182 of an inbound distributed storageand task (DST) processing section. The DS error decoding module 182includes an inverse per slice security processing module 202, ade-slicing module 204, an error decoding module 206, an inverse segmentsecurity module 208, a de-segmenting processing module 210, and acontrol module 186.

In an example of operation, the inverse per slice security processingmodule 202, when enabled by the control module 186, unsecures eachencoded data slice 122 based on slice de-security information receivedas control information 190 (e.g., the compliment of the slice securityinformation discussed with reference to FIG. 6) received from thecontrol module 186. The slice security information includes datadecompression, decryption, de-watermarking, integrity check (e.g., CRCverification, etc.), and/or any other type of digital security. Forexample, when the inverse per slice security processing module 202 isenabled, it verifies integrity information (e.g., a CRC value) of eachencoded data slice 122, it decrypts each verified encoded data slice,and decompresses each decrypted encoded data slice to produce sliceencoded data 158. When the inverse per slice security processing module202 is not enabled, it passes the encoded data slices 122 as the slicedencoded data 158 or is bypassed such that the retrieved encoded dataslices 122 are provided as the sliced encoded data 158.

The de-slicing module 204 de-slices the sliced encoded data 158 intoencoded data segments 156 in accordance with a pillar width of the errorcorrection encoding parameters received as control information 190 fromthe control module 186. For example, if the pillar width is five, thede-slicing module 204 de-slices a set of five encoded data slices intoan encoded data segment 156. The error decoding module 206 decodes theencoded data segments 156 in accordance with error correction decodingparameters received as control information 190 from the control module186 to produce secure data segments 154. The error correction decodingparameters include identifying an error correction encoding scheme(e.g., forward error correction algorithm, a Reed-Solomon basedalgorithm, an information dispersal algorithm, etc.), a pillar width, adecode threshold, a read threshold, a write threshold, etc. For example,the error correction decoding parameters identify a specific errorcorrection encoding scheme, specify a pillar width of five, and specifya decode threshold of three.

The inverse segment security processing module 208, when enabled by thecontrol module 186, unsecures the secured data segments 154 based onsegment security information received as control information 190 fromthe control module 186. The segment security information includes datadecompression, decryption, de-watermarking, integrity check (e.g., CRC,etc.) verification, and/or any other type of digital security. Forexample, when the inverse segment security processing module 208 isenabled, it verifies integrity information (e.g., a CRC value) of eachsecure data segment 154, it decrypts each verified secured data segment,and decompresses each decrypted secure data segment to produce a datasegment 152. When the inverse segment security processing module 208 isnot enabled, it passes the decoded data segment 154 as the data segment152 or is bypassed.

The de-segment processing module 210 receives the data segments 152 andreceives de-segmenting information as control information 190 from thecontrol module 186. The de-segmenting information indicates how thede-segment processing module 210 is to de-segment the data segments 152into a data partition 120. For example, the de-segmenting informationindicates how the rows and columns of data segments are to be rearrangedto yield the data partition 120.

FIG. 17 is a diagram of an example of de-slicing and error decodingprocessing of a dispersed error decoding module. A de-slicing module 204receives at least a decode threshold number of encoded data slices 158for each data segment in accordance with control information 190 andprovides encoded data 156. In this example, a decode threshold is three.As such, each set of encoded data slices 158 is shown to have threeencoded data slices per data segment. The de-slicing module 204 mayreceive three encoded data slices per data segment because an associateddistributed storage and task (DST) client module requested retrievingonly three encoded data slices per segment or selected three of theretrieved encoded data slices per data segment. As shown, which is basedon the unity matrix encoding previously discussed with reference to FIG.8, an encoded data slice may be a data-based encoded data slice (e.g.,DS1 _(—) d 1&d2) or an error code based encoded data slice (e.g.,ES3_1).

An error decoding module 206 decodes the encoded data 156 of each datasegment in accordance with the error correction decoding parameters ofcontrol information 190 to produce secured segments 154. In thisexample, data segment 1 includes 3 rows with each row being treated asone word for encoding. As such, data segment 1 includes three words:word 1 including data blocks d1 and d2, word 2 including data blocks d16and d17, and word 3 including data blocks d31 and d32. Each of datasegments 2-7 includes three words where each word includes two datablocks. Data segment 8 includes three words where each word includes asingle data block (e.g., d15, d30, and d45).

FIG. 18 is a diagram of an example of de-segment processing of aninbound distributed storage and task (DST) processing. In this example,a de-segment processing module 210 receives data segments 152 (e.g.,1-8) and rearranges the data blocks of the data segments into rows andcolumns in accordance with de-segmenting information of controlinformation 190 to produce a data partition 120. Note that the number ofrows is based on the decode threshold (e.g., 3 in this specific example)and the number of columns is based on the number and size of the datablocks.

The de-segmenting module 210 converts the rows and columns of datablocks into the data partition 120. Note that each data block may be ofthe same size as other data blocks or of a different size. In addition,the size of each data block may be a few bytes to megabytes of data.

FIG. 19 is a diagram of an example of converting slice groups into data92 within an inbound distributed storage and task (DST) processingsection. As shown, the data 92 is reconstructed from a plurality of datapartitions (1−x, where x is an integer greater than 4). Each datapartition (or chunk set of data) is decoded and re-grouped using ade-grouping and decoding function 212 and a de-partition function 214from slice groupings as previously discussed. For a given datapartition, the slice groupings (e.g., at least a decode threshold perdata segment of encoded data slices) are received from DST executionunits. From data partition to data partition, the ordering of the slicegroupings received from the DST execution units may vary as discussedwith reference to FIG. 10.

FIG. 20 is a diagram of an example of a distributed storage and/orretrieval within the distributed computing system. The distributedcomputing system includes a plurality of distributed storage and/or task(DST) processing client modules 34 (one shown) coupled to a distributedstorage and/or task processing network (DSTN) module, or multiple DSTNmodules, via a network 24. The DST client module 34 includes an outboundDST processing section 80 and an inbound DST processing section 82. TheDSTN module includes a plurality of DST execution units. Each DSTexecution unit includes a controller 86, memory 88, one or moredistributed task (DT) execution modules 90, and a DST client module 34.

In an example of data storage, the DST client module 34 has data 92 thatit desires to store in the DSTN module. The data 92 may be a file (e.g.,video, audio, text, graphics, etc.), a data object, a data block, anupdate to a file, an update to a data block, etc. In this instance, theoutbound DST processing module 80 converts the data 92 into encoded dataslices 216 as will be further described with reference to FIGS. 21-23.The outbound DST processing module 80 sends, via the network 24, to theDST execution units for storage as further described with reference toFIG. 24.

In an example of data retrieval, the DST client module 34 issues aretrieve request to the DST execution units for the desired data 92. Theretrieve request may address each DST executions units storing encodeddata slices of the desired data, address a decode threshold number ofDST execution units, address a read threshold number of DST executionunits, or address some other number of DST execution units. In responseto the request, each addressed

DST execution unit retrieves its encoded data slices 100 of the desireddata and sends them to the inbound DST processing section 82, via thenetwork 24.

When, for each data segment, the inbound DST processing section 82receives at least a decode threshold number of encoded data slices 100,it converts the encoded data slices 100 into a data segment. The inboundDST processing section 82 aggregates the data segments to produce theretrieved data 92.

FIG. 21 is a schematic block diagram of an embodiment of an outbounddistributed storage and/or task (DST) processing section 80 of a DSTclient module coupled to a distributed storage and task network (DSTN)module (e.g., a plurality of DST execution units) via a network 24. Theoutbound DST processing section 80 includes a data partitioning module110, a dispersed storage (DS) error encoding module 112, a groupingselector module 114, a control module 116, and a distributed taskcontrol module 118.

In an example of operation, the data partitioning module 110 isby-passed such that data 92 is provided directly to the DS errorencoding module 112. The control module 116 coordinates the by-passingof the data partitioning module 110 by outputting a bypass 220 messageto the data partitioning module 110.

The DS error encoding module 112 receives the data 92 in a serialmanner, a parallel manner, and/or a combination thereof. The DS errorencoding module 112 DS error encodes the data in accordance with controlinformation 160 from the control module 116 to produce encoded dataslices 218. The DS error encoding includes segmenting the data 92 intodata segments, segment security processing (e.g., encryption,compression, watermarking, integrity check (e.g., CRC, etc.)), errorencoding, slicing, and/or per slice security processing (e.g.,encryption, compression, watermarking, integrity check (e.g., CRC,etc.)). The control information 160 indicates which steps of the DSerror encoding are active for the data 92 and, for active steps,indicates the parameters for the step. For example, the controlinformation 160 indicates that the error encoding is active and includeserror encoding parameters (e.g., pillar width, decode threshold, writethreshold, read threshold, type of error encoding, etc.).

The grouping selector module 114 groups the encoded slices 218 of thedata segments into pillars of slices 216. The number of pillarscorresponds to the pillar width of the DS error encoding parameters. Inthis example, the distributed task control module 118 facilitates thestorage request.

FIG. 22 is a schematic block diagram of an example of a dispersedstorage (DS) error encoding module 112 for the example of FIG. 21. TheDS error encoding module 112 includes a segment processing module 142, asegment security processing module 144, an error encoding module 146, aslicing module 148, and a per slice security processing module 150. Eachof these modules is coupled to a control module 116 to receive controlinformation 160 therefrom.

In an example of operation, the segment processing module 142 receivesdata 92 and receives segmenting information as control information 160from the control module 116. The segmenting information indicates howthe segment processing module is to segment the data. For example, thesegmenting information indicates the size of each data segment. Thesegment processing module 142 segments the data 92 into data segments152 in accordance with the segmenting information.

The segment security processing module 144, when enabled by the controlmodule 116, secures the data segments 152 based on segment securityinformation received as control information 160 from the control module116. The segment security information includes data compression,encryption, watermarking, integrity check (e.g., CRC, etc.), and/or anyother type of digital security. For example, when the segment securityprocessing module 144 is enabled, it compresses a data segment 152,encrypts the compressed data segment, and generates a CRC value for theencrypted data segment to produce a secure data segment. When thesegment security processing module 144 is not enabled, it passes thedata segments 152 to the error encoding module 146 or is bypassed suchthat the data segments 152 are provided to the error encoding module146.

The error encoding module 146 encodes the secure data segments inaccordance with error correction encoding parameters received as controlinformation 160 from the control module 116. The error correctionencoding parameters include identifying an error correction encodingscheme (e.g., forward error correction algorithm, a Reed-Solomon basedalgorithm, an information dispersal algorithm, etc.), a pillar width, adecode threshold, a read threshold, a write threshold, etc. For example,the error correction encoding parameters identify a specific errorcorrection encoding scheme, specifies a pillar width of five, andspecifies a decode threshold of three. From these parameters, the errorencoding module 146 encodes a data segment to produce an encoded datasegment.

The slicing module 148 slices the encoded data segment in accordancewith a pillar width of the error correction encoding parameters. Forexample, if the pillar width is five, the slicing module slices anencoded data segment into a set of five encoded data slices. As such,for a plurality of data segments, the slicing module 148 outputs aplurality of sets of encoded data slices as shown within encoding andslicing function 222 as described.

The per slice security processing module 150, when enabled by thecontrol module 116, secures each encoded data slice based on slicesecurity information received as control information 160 from thecontrol module 116. The slice security information includes datacompression, encryption, watermarking, integrity check (e.g., CRC,etc.), and/or any other type of digital security. For example, when theper slice security processing module 150 is enabled, it may compress anencoded data slice, encrypt the compressed encoded data slice, andgenerate a CRC value for the encrypted encoded data slice to produce asecure encoded data slice tweaking. When the per slice securityprocessing module 150 is not enabled, it passes the encoded data slicesor is bypassed such that the encoded data slices 218 are the output ofthe DS error encoding module 112.

FIG. 23 is a diagram of an example of converting data 92 into pillarslice groups utilizing encoding, slicing and pillar grouping function224 for storage in memory of a distributed storage and task network(DSTN) module. As previously discussed the data 92 is encoded and slicedinto a plurality of sets of encoded data slices; one set per datasegment. The grouping selection module organizes the sets of encodeddata slices into pillars of data slices. In this example, the DS errorencoding parameters include a pillar width of 5 and a decode thresholdof 3. As such, for each data segment, 5 encoded data slices are created.

The grouping selection module takes the first encoded data slice of eachof the sets and forms a first pillar, which may be sent to the first DSTexecution unit. Similarly, the grouping selection module creates thesecond pillar from the second slices of the sets; the third pillar fromthe third slices of the sets; the fourth pillar from the fourth slicesof the sets; and the fifth pillar from the fifth slices of the set.

FIG. 24 is a schematic block diagram of an embodiment of a distributedstorage and/or task (DST) execution unit that includes an interface 169,a controller 86, memory 88, one or more distributed task (DT) executionmodules 90, and a DST client module 34. A computing core 26 may beutilized to implement the one or more DT execution modules 90 and theDST client module 34. The memory 88 is of sufficient size to store asignificant number of encoded data slices (e.g., thousands of slices tohundreds-of-millions of slices) and may include one or more hard drivesand/or one or more solid-state memory devices (e.g., flash memory, DRAM,etc.).

In an example of storing a pillar of slices 216, the DST execution unitreceives, via interface 169, a pillar of slices 216 (e.g., pillar #1slices). The memory 88 stores the encoded data slices 216 of the pillarof slices in accordance with memory control information 174 it receivesfrom the controller 86. The controller 86 (e.g., a processing module, aCPU, etc.) generates the memory control information 174 based ondistributed storage information (e.g., user information (e.g., user ID,distributed storage permissions, data access permission, etc.), vaultinformation (e.g., virtual memory assigned to user, user group, etc.),etc.). Similarly, when retrieving slices, the DST execution unitreceives, via interface 169, a slice retrieval request. The memory 88retrieves the slice in accordance with memory control information 174 itreceives from the controller 86. The memory 88 outputs the slice 100,via the interface 169, to a requesting entity.

FIG. 25 is a schematic block diagram of an example of operation of aninbound distributed storage and/or task (DST) processing section 82 forretrieving dispersed error encoded data 92. The inbound DST processingsection 82 includes a de-grouping module 180, a dispersed storage (DS)error decoding module 182, a data de-partitioning module 184, a controlmodule 186, and a distributed task control module 188. Note that thecontrol module 186 and/or the distributed task control module 188 may beseparate modules from corresponding ones of an outbound DST processingsection or may be the same modules.

In an example of operation, the inbound DST processing section 82 isretrieving stored data 92 from the DST execution units (i.e., the DSTNmodule). In this example, the DST execution units output encoded dataslices corresponding to data retrieval requests from the distributedtask control module 188. The de-grouping module 180 receives pillars ofslices 100 and de-groups them in accordance with control information 190from the control module 186 to produce sets of encoded data slices 218.The DS error decoding module 182 decodes, in accordance with the DSerror encoding parameters received as control information 190 from thecontrol module 186, each set of encoded data slices 218 to produce datasegments, which are aggregated into retrieved data 92. The datade-partitioning module 184 is by-passed in this operational mode via abypass signal 226 of control information 190 from the control module186.

FIG. 26 is a schematic block diagram of an embodiment of a dispersedstorage (DS) error decoding module 182 of an inbound distributed storageand task (DST) processing section. The DS error decoding module 182includes an inverse per slice security processing module 202, ade-slicing module 204, an error decoding module 206, an inverse segmentsecurity module 208, and a de-segmenting processing module 210. Thedispersed error decoding module 182 is operable to de-slice and decodeencoded slices per data segment 218 utilizing a de-slicing and decodingfunction 228 to produce a plurality of data segments that arede-segmented utilizing a de-segment function 230 to recover data 92.

In an example of operation, the inverse per slice security processingmodule 202, when enabled by the control module 186 via controlinformation 190, unsecures each encoded data slice 218 based on slicede-security information (e.g., the compliment of the slice securityinformation discussed with reference to FIG. 6) received as controlinformation 190 from the control module 186. The slice de-securityinformation includes data decompression, decryption, de-watermarking,integrity check (e.g., CRC verification, etc.), and/or any other type ofdigital security. For example, when the inverse per slice securityprocessing module 202 is enabled, it verifies integrity information(e.g., a CRC value) of each encoded data slice 218, it decrypts eachverified encoded data slice, and decompresses each decrypted encodeddata slice to produce slice encoded data. When the inverse per slicesecurity processing module 202 is not enabled, it passes the encodeddata slices 218 as the sliced encoded data or is bypassed such that theretrieved encoded data slices 218 are provided as the sliced encodeddata.

The de-slicing module 204 de-slices the sliced encoded data into encodeddata segments in accordance with a pillar width of the error correctionencoding parameters received as control information 190 from a controlmodule 186. For example, if the pillar width is five, the de-slicingmodule de-slices a set of five encoded data slices into an encoded datasegment. Alternatively, the encoded data segment may include just threeencoded data slices (e.g., when the decode threshold is 3).

The error decoding module 206 decodes the encoded data segments inaccordance with error correction decoding parameters received as controlinformation 190 from the control module 186 to produce secure datasegments. The error correction decoding parameters include identifyingan error correction encoding scheme (e.g., forward error correctionalgorithm, a Reed-Solomon based algorithm, an information dispersalalgorithm, etc.), a pillar width, a decode threshold, a read threshold,a write threshold, etc. For example, the error correction decodingparameters identify a specific error correction encoding scheme, specifya pillar width of five, and specify a decode threshold of three.

The inverse segment security processing module 208, when enabled by thecontrol module 186, unsecures the secured data segments based on segmentsecurity information received as control information 190 from thecontrol module 186. The segment security information includes datadecompression, decryption, de-watermarking, integrity check (e.g., CRC,etc.) verification, and/or any other type of digital security. Forexample, when the inverse segment security processing module is enabled,it verifies integrity information (e.g., a CRC value) of each securedata segment, it decrypts each verified secured data segment, anddecompresses each decrypted secure data segment to produce a datasegment 152. When the inverse segment security processing module 208 isnot enabled, it passes the decoded data segment 152 as the data segmentor is bypassed. The de-segmenting processing module 210 aggregates thedata segments 152 into the data 92 in accordance with controlinformation 190 from the control module 186.

FIG. 27 is a schematic block diagram of an example of a distributedstorage and task processing network (DSTN) module that includes aplurality of distributed storage and task (DST) execution units (#1through #n, where, for example, n is an integer greater than or equal tothree). Each of the DST execution units includes a DST client module 34,a controller 86, one or more DT (distributed task) execution modules 90,and memory 88.

In this example, the DSTN module stores, in the memory of the DSTexecution units, a plurality of DS (dispersed storage) encoded data(e.g., 1 through n, where n is an integer greater than or equal to two)and stores a plurality of DS encoded task codes (e.g., 1 through k,where k is an integer greater than or equal to two). The DS encoded datamay be encoded in accordance with one or more examples described withreference to FIGS. 3-19 (e.g., organized in slice groupings) or encodedin accordance with one or more examples described with reference toFIGS. 20-26 (e.g., organized in pillar groups). The data that is encodedinto the DS encoded data may be of any size and/or of any content. Forexample, the data may be one or more digital books, a copy of acompany's emails, a large-scale Internet search, a video security file,one or more entertainment video files (e.g., television programs,movies, etc.), data files, and/or any other large amount of data (e.g.,greater than a few Terabytes).

The tasks that are encoded into the DS encoded task code may be a simplefunction (e.g., a mathematical function, a logic function, an identifyfunction, a find function, a search engine function, a replace function,etc.), a complex function (e.g., compression, human and/or computerlanguage translation, text-to-voice conversion, voice-to-textconversion, etc.), multiple simple and/or complex functions, one or morealgorithms, one or more applications, etc. The tasks may be encoded intothe DS encoded task code in accordance with one or more examplesdescribed with reference to FIGS. 3-19 (e.g., organized in slicegroupings) or encoded in accordance with one or more examples describedwith reference to FIGS. 20-26 (e.g., organized in pillar groups).

In an example of operation, a DST client module of a user device or of aDST processing unit issues a DST request to the DSTN module. The DSTrequest may include a request to retrieve stored data, or a portionthereof, may include a request to store data that is included with theDST request, may include a request to perform one or more tasks onstored data, may include a request to perform one or more tasks on dataincluded with the DST request, etc. In the cases where the DST requestincludes a request to store data or to retrieve data, the client moduleand/or the DSTN module processes the request as previously discussedwith reference to one or more of FIGS. 3-19 (e.g., slice groupings)and/or 20-26 (e.g., pillar groupings). In the case where the DST requestincludes a request to perform one or more tasks on data included withthe DST request, the DST client module and/or the DSTN module processthe DST request as previously discussed with reference to one or more ofFIGS. 3-19.

In the case where the DST request includes a request to perform one ormore tasks on stored data, the DST client module and/or the DSTN moduleprocesses the DST request as will be described with reference to one ormore of FIGS. 28-39. In general, the DST client module identifies dataand one or more tasks for the DSTN module to execute upon the identifieddata. The DST request may be for a one-time execution of the task or foran on-going execution of the task. As an example of the latter, as acompany generates daily emails, the DST request may be to daily searchnew emails for inappropriate content and, if found, record the content,the email sender(s), the email recipient(s), email routing information,notify human resources of the identified email, etc.

FIG. 28 is a schematic block diagram of an example of a distributedcomputing system performing tasks on stored data. In this example, twodistributed storage and task (DST) client modules 1-2 are shown: thefirst may be associated with a user device and the second may beassociated with a DST processing unit or a high priority user device(e.g., high priority clearance user, system administrator, etc.). EachDST client module includes a list of stored data 234 and a list of taskscodes 236. The list of stored data 234 includes one or more entries ofdata identifying information, where each entry identifies data stored inthe DSTN module 22. The data identifying information (e.g., data ID)includes one or more of a data file name, a data file directory listing,DSTN addressing information of the data, a data object identifier, etc.The list of tasks 236 includes one or more entries of task codeidentifying information, when each entry identifies task codes stored inthe DSTN module 22. The task code identifying information (e.g., taskID) includes one or more of a task file name, a task file directorylisting, DSTN addressing information of the task, another type ofidentifier to identify the task, etc.

As shown, the list of data 234 and the list of tasks 236 are eachsmaller in number of entries for the first DST client module than thecorresponding lists of the second DST client module. This may occurbecause the user device associated with the first DST client module hasfewer privileges in the distributed computing system than the deviceassociated with the second DST client module. Alternatively, this mayoccur because the user device associated with the first DST clientmodule serves fewer users than the device associated with the second DSTclient module and is restricted by the distributed computing systemaccordingly. As yet another alternative, this may occur through norestraints by the distributed computing system, it just occurred becausethe operator of the user device associated with the first DST clientmodule has selected fewer data and/or fewer tasks than the operator ofthe device associated with the second DST client module.

In an example of operation, the first DST client module selects one ormore data entries 238 and one or more tasks 240 from its respectivelists (e.g., selected data ID and selected task ID). The first DSTclient module sends its selections to a task distribution module 232.The task distribution module 232 may be within a stand-alone device ofthe distributed computing system, may be within the user device thatcontains the first DST client module, or may be within the DSTN module22.

Regardless of the task distribution module's location, it generates DSTallocation information 242 from the selected task ID 240 and theselected data ID 238. The DST allocation information 242 includes datapartitioning information, task execution information, and/orintermediate result information. The task distribution module 232 sendsthe DST allocation information 242 to the DSTN module 22. Note that oneor more examples of the DST allocation information will be discussedwith reference to one or more of FIGS. 29-39.

The DSTN module 22 interprets the DST allocation information 242 toidentify the stored DS encoded data (e.g., DS error encoded data 2) andto identify the stored DS error encoded task code (e.g., DS errorencoded task code 1). In addition, the DSTN module 22 interprets the DSTallocation information 242 to determine how the data is to bepartitioned and how the task is to be partitioned. The DSTN module 22also determines whether the selected DS error encoded data 238 needs tobe converted from pillar grouping to slice grouping. If so, the DSTNmodule 22 converts the selected DS error encoded data into slicegroupings and stores the slice grouping DS error encoded data byoverwriting the pillar grouping DS error encoded data or by storing itin a different location in the memory of the DSTN module 22 (i.e., doesnot overwrite the pillar grouping DS encoded data).

The DSTN module 22 partitions the data and the task as indicated in theDST allocation information 242 and sends the portions to selected DSTexecution units of the DSTN module 22. Each of the selected DSTexecution units performs its partial task(s) on its slice groupings toproduce partial results. The DSTN module 22 collects the partial resultsfrom the selected DST execution units and provides them, as resultinformation 244, to the task distribution module. The result information244 may be the collected partial results, one or more final results asproduced by the DSTN module 22 from processing the partial results inaccordance with the DST allocation information 242, or one or moreintermediate results as produced by the DSTN module 22 from processingthe partial results in accordance with the DST allocation information242.

The task distribution module 232 receives the result information 244 andprovides one or more final results 104 therefrom to the first DST clientmodule. The final result(s) 104 may be result information 244 or aresult(s) of the task distribution module's processing of the resultinformation 244.

In concurrence with processing the selected task of the first DST clientmodule, the distributed computing system may process the selectedtask(s) of the second DST client module on the selected data(s) of thesecond DST client module. Alternatively, the distributed computingsystem may process the second DST client module's request subsequent to,or preceding, that of the first DST client module. Regardless of theordering and/or parallel processing of the DST client module requests,the second DST client module provides its selected data 238 and selectedtask 240 to a task distribution module 232. If the task distributionmodule 232 is a separate device of the distributed computing system orwithin the DSTN module, the task distribution modules 232 coupled to thefirst and second DST client modules may be the same module. The taskdistribution module 232 processes the request of the second DST clientmodule in a similar manner as it processed the request of the first DSTclient module.

FIG. 29 is a schematic block diagram of an embodiment of a taskdistribution module 232 facilitating the example of FIG. 28. The taskdistribution module 232 includes a plurality of tables it uses togenerate distributed storage and task (DST) allocation information 242for selected data and selected tasks received from a DST client module.The tables include data storage information 248, task storageinformation 250, distributed task (DT) execution module information 252,and task ⇄ sub-task mapping information 246.

The data storage information table 248 includes a data identification(ID) field 260, a data size field 262, an addressing information field264, distributed storage (DS) information 266, and may further includeother information regarding the data, how it is stored, and/or how itcan be processed. For example, DS encoded data #1 has a data ID of 1, adata size of AA (e.g., a byte size of a few Terabytes or more),addressing information of Addr_1_AA, and DS parameters of 3/5; SEG_1;and SLC_1. In this example, the addressing information may be a virtualaddress corresponding to the virtual address of the first storage word(e.g., one or more bytes) of the data and information on how tocalculate the other addresses, may be a range of virtual addresses forthe storage words of the data, physical addresses of the first storageword or the storage words of the data, may be a list of slice names ofthe encoded data slices of the data, etc. The DS parameters may includeidentity of an error encoding scheme, decode threshold/pillar width(e.g., 3/5 for the first data entry), segment security information(e.g., SEG_1), per slice security information (e.g., SLC_1), and/or anyother information regarding how the data was encoded into data slices.

The task storage information table 250 includes a task identification(ID) field 268, a task size field 270, an addressing information field272, distributed storage (DS) information 274, and may further includeother information regarding the task, how it is stored, and/or how itcan be used to process data. For example, DS encoded task #2 has a taskID of 2, a task size of XY, addressing information of Addr_2_XY, and DSparameters of 3/5; SEG_2; and SLC_2. In this example, the addressinginformation may be a virtual address corresponding to the virtualaddress of the first storage word (e.g., one or more bytes) of the taskand information on how to calculate the other addresses, may be a rangeof virtual addresses for the storage words of the task, physicaladdresses of the first storage word or the storage words of the task,may be a list of slices names of the encoded slices of the task code,etc. The DS parameters may include identity of an error encoding scheme,decode threshold/pillar width (e.g., 3/5 for the first data entry),segment security information (e.g., SEG_2), per slice securityinformation (e.g., SLC_2), and/or any other information regarding howthe task was encoded into encoded task slices. Note that the segmentand/or the per-slice security information include a type of encryption(if enabled), a type of compression (if enabled), watermarkinginformation (if enabled), and/or an integrity check scheme (if enabled).

The task ⇄ sub-task mapping information table 246 includes a task field256 and a sub-task field 258. The task field 256 identifies a taskstored in the memory of a distributed storage and task network (DSTN)module and the corresponding sub-task fields 258 indicates whether thetask includes sub-tasks and, if so, how many and if any of the sub-tasksare ordered. In this example, the task ⇄ sub-task mapping informationtable 246 includes an entry for each task stored in memory of the DSTNmodule (e.g., task 1 through task k). In particular, this exampleindicates that task 1 includes 7 sub-tasks; task 2 does not includesub-tasks, and task k includes r number of sub-tasks (where r is aninteger greater than or equal to two).

The DT execution module table 252 includes a DST execution unit ID field276, a DT execution module ID field 278, and a DT execution modulecapabilities field 280. The DST execution unit ID field 276 includes theidentity of DST units in the DSTN module. The DT execution module IDfield 278 includes the identity of each DT execution unit in each DSTunit. For example, DST unit 1 includes three DT executions modules(e.g., 1_1, 1_2, and 1_3). The DT execution capabilities field 280includes identity of the capabilities of the corresponding DT executionunit. For example, DT execution module 1_1 includes capabilities X,where X includes one or more of MIPS capabilities, processing resources(e.g., quantity and capability of microprocessors, CPUs, digital signalprocessors, co-processor, microcontrollers, arithmetic logic circuitry,and/or any other analog and/or digital processing circuitry),availability of the processing resources, memory information (e.g.,type, size, availability, etc.), and/or any information germane toexecuting one or more tasks.

From these tables, the task distribution module 232 generates the DSTallocation information 242 to indicate where the data is stored, how topartition the data, where the task is stored, how to partition the task,which DT execution units should perform which partial task on which datapartitions, where and how intermediate results are to be stored, etc. Ifmultiple tasks are being performed on the same data or different data,the task distribution module factors such information into itsgeneration of the DST allocation information.

FIG. 30 is a diagram of a specific example of a distributed computingsystem performing tasks on stored data as a task flow 318. In thisexample, selected data 92 is data 2 and selected tasks are tasks 1, 2,and 3. Task 1 corresponds to analyzing translation of data from onelanguage to another (e.g., human language or computer language); task 2corresponds to finding specific words and/or phrases in the data; andtask 3 corresponds to finding specific translated words and/or phrasesin translated data.

In this example, task 1 includes 7 sub-tasks: task 1_1—identifynon-words (non-ordered); task 1_2—identify unique words (non-ordered);task 1_3—translate (non-ordered); task 1_4-translate back (ordered aftertask 1_3); task 1_5—compare to ID errors (ordered after task 1-4); task1_6—determine non-word translation errors (ordered after task 1_5 and1_1); and task 1_7-determine correct translations (ordered after 1_5 and1_2). The sub-task further indicates whether they are an ordered task(i.e., are dependent on the outcome of another task) or non-order (i.e.,are independent of the outcome of another task). Task 2 does not includesub-tasks and task 3 includes two sub-tasks: task 3_1 translate; andtask 3_2 find specific word or phrase in translated data.

In general, the three tasks collectively are selected to analyze datafor translation accuracies, translation errors, translation anomalies,occurrence of specific words or phrases in the data, and occurrence ofspecific words or phrases on the translated data. Graphically, the data92 is translated 306 into translated data 282; is analyzed for specificwords and/or phrases 300 to produce a list of specific words and/orphrases 286; is analyzed for non-words 302 (e.g., not in a referencedictionary) to produce a list of non-words 290; and is analyzed forunique words 316 included in the data 92 (i.e., how many different wordsare included in the data) to produce a list of unique words 298. Each ofthese tasks is independent of each other and can therefore be processedin parallel if desired.

The translated data 282 is analyzed (e.g., sub-task 3_2) for specifictranslated words and/or phrases 304 to produce a list of specifictranslated words and/or phrases. The translated data 282 is translatedback 308 (e.g., sub-task 1_4) into the language of the original data toproduce re-translated data 284. These two tasks are dependent on thetranslate task (e.g., task 1_3) and thus must be ordered after thetranslation task, which may be in a pipelined ordering or a serialordering. The re-translated data 284 is then compared 310 with theoriginal data 92 to find words and/or phrases that did not translate(one way and/or the other) properly to produce a list of incorrectlytranslated words 294. As such, the comparing task (e.g., sub-task 1_5)310 is ordered after the translation 306 and re-translation tasks 308(e.g., sub-tasks 1_3 and 1_4).

The list of words incorrectly translated 294 is compared 312 to the listof non-words 290 to identify words that were not properly translatedbecause the words are non-words to produce a list of errors due tonon-words 292. In addition, the list of words incorrectly translated 294is compared 314 to the list of unique words 298 to identify unique wordsthat were properly translated to produce a list of correctly translatedwords 296. The comparison may also identify unique words that were notproperly translated to produce a list of unique words that were notproperly translated. Note that each list of words (e.g., specific wordsand/or phrases, non-words, unique words, translated words and/orphrases, etc.,) may include the word and/or phrase, how many times it isused, where in the data it is used, and/or any other informationrequested regarding a word and/or phrase.

FIG. 31 is a schematic block diagram of an example of a distributedstorage and task processing network (DSTN) module storing data and taskcodes for the example of FIG. 30. As shown, DS encoded data 2 is storedas encoded data slices across the memory (e.g., stored in memories 88)of DST execution units 1-5; the DS encoded task code 1 (of task 1) andDS encoded task 3 are stored as encoded task slices across the memory ofDST execution units 1-5; and DS encoded task code 2 (of task 2) isstored as encoded task slices across the memory of DST execution units3-7. As indicated in the data storage information table and the taskstorage information table of FIG. 29, the respective data/task has DSparameters of 3/5 for their decode threshold/pillar width; hencespanning the memory of five DST execution units.

FIG. 32 is a diagram of an example of distributed storage and task (DST)allocation information 242 for the example of FIG. 30. The DSTallocation information 242 includes data partitioning information 320,task execution information 322, and intermediate result information 324.The data partitioning information 320 includes the data identifier (ID),the number of partitions to split the data into, address information foreach data partition, and whether the DS encoded data has to betransformed from pillar grouping to slice grouping. The task executioninformation 322 includes tabular information having a taskidentification field 326, a task ordering field 328, a data partitionfield ID 330, and a set of DT execution modules 332 to use for thedistributed task processing per data partition. The intermediate resultinformation 324 includes tabular information having a name ID field 334,an ID of the DST execution unit assigned to process the correspondingintermediate result 336, a scratch pad storage field 338, and anintermediate result storage field 340.

Continuing with the example of FIG. 30, where tasks 1-3 are to bedistributedly performed on data 2, the data partitioning informationincludes the ID of data 2. In addition, the task distribution moduledetermines whether the DS encoded data 2 is in the proper format fordistributed computing (e.g., was stored as slice groupings). If not, thetask distribution module indicates that the DS encoded data 2 formatneeds to be changed from the pillar grouping format to the slicegrouping format, which will be done the by DSTN module. In addition, thetask distribution module determines the number of partitions to dividethe data into (e.g., 2_1 through 2 _(—) z) and addressing informationfor each partition.

The task distribution module generates an entry in the task executioninformation section for each sub-task to be performed. For example, task1_1 (e.g., identify non-words on the data) has no task ordering (i.e.,is independent of the results of other sub-tasks), is to be performed ondata partitions 2_1 through 2 _(—) zby DT execution modules 1_1, 2_1,3_1, 4_1, and 5_1. For instance, DT execution modules 1_1, 2_1, 3_1,4_1, and 5_1 search for non-words in data partitions 2_1 through 2 _(—)zto produce task 1_1 intermediate results (R1-1, which is a list ofnon-words). Task 1_2 (e.g., identify unique words) has similar taskexecution information as task 1_1 to produce task 1_2 intermediateresults (R1-2, which is the list of unique words).

Task 1_3 (e.g., translate) includes task execution information as beingnon-ordered (i.e., is independent), having DT execution modules 1_1,2_1, 3_1, 4_1, and 5_1 translate data partitions 2_1 through 2_4 andhaving DT execution modules 1_2, 2_2, 3_2, 4_2, and 5_2 translate datapartitions 2_5 through 2 _(—) zto produce task 1_3 intermediate results(R1-3, which is the translated data). In this example, the datapartitions are grouped, where different sets of DT execution modulesperform a distributed sub-task (or task) on each data partition group,which allows for further parallel processing.

Task 1_4 (e.g., translate back) is ordered after task 1_3 and is to beexecuted on task 1_3's intermediate result (e.g., R1-3_1) (e.g., thetranslated data). DT execution modules 1_1, 2_1, 3_1, 4_1, and 5_1 areallocated to translate back task 1_3 intermediate result partitionsR1-3_1 through R1-3_4 and DT execution modules 1_2, 2_2, 6_1, 7_1, and7_2 are allocated to translate back task 1_3 intermediate resultpartitions R1-3_5 through R1-3 _(—) zto produce task 1-4 intermediateresults (R1-4, which is the translated back data).

Task 1_5 (e.g., compare data and translated data to identify translationerrors) is ordered after task 1_4 and is to be executed on task 1_4'sintermediate results (R4-1) and on the data. DT execution modules 1_1,2_1, 3_1, 4_1, and 5_1 are allocated to compare the data partitions (2_1through 2 _(—) z) with partitions of task 1-4 intermediate resultspartitions R1-4_1 through R1-4 _(—) zto produce task 1_5 intermediateresults (R1-5, which is the list words translated incorrectly).

Task 1_6 (e.g., determine non-word translation errors) is ordered aftertasks 1_1 and 1_5 and is to be executed on tasks 1_1's and 1_5'sintermediate results (R1-1 and R1-5). DT execution modules 1_1, 2_1,3_1, 4_1, and 5_1 are allocated to compare the partitions of task 1_1intermediate results (R1-1_1 through R1-1 _(—) z) with partitions oftask 1-5 intermediate results partitions (R1-5_1 through R1-5 _(—) z) toproduce task 1_6 intermediate results (R1-6, which is the listtranslation errors due to non-words).

Task 1_7 (e.g., determine words correctly translated) is ordered aftertasks 1_2 and 1_5 and is to be executed on tasks 1_2's and 1_5'sintermediate results (R1-1 and R1-5). DT execution modules 1_2, 2_2,3_2, 4_2, and 5_2 are allocated to compare the partitions of task 1_2intermediate results (R1-2_1 through R1-2 _(—) z) with partitions oftask 1-5 intermediate results partitions (R1-5_1 through R1-5 _(—) z) toproduce task 1_7 intermediate results (R1-7, which is the list ofcorrectly translated words).

Task 2 (e.g., find specific words and/or phrases) has no task ordering(i.e., is independent of the results of other sub-tasks), is to beperformed on data partitions 2_1 through 2 _(—) zby DT execution modules3_1, 4_1, 5_1, 6_1, and 7_1. For instance, DT execution modules 3_1,4_1, 5_1, 6_1, and 7_1 search for specific words and/or phrases in datapartitions 2_1 through 2 _(—) zto produce task 2 intermediate results(R2, which is a list of specific words and/or phrases).

Task 3_2 (e.g., find specific translated words and/or phrases) isordered after task 1_3 (e.g., translate) is to be performed onpartitions R1-3_1 through R1-3 _(—) zby DT execution modules 1_2, 2_2,3_2, 4_2, and 5_2. For instance, DT execution modules 1_2, 2_2, 3_2,4_2, and 5_2 search for specific translated words and/or phrases in thepartitions of the translated data (R1-3_1 through R1-3 _(—) z) toproduce task 3_2 intermediate results (R3-2, which is a list of specifictranslated words and/or phrases).

For each task, the intermediate result information indicates which DSTunit is responsible for overseeing execution of the task and, if needed,processing the partial results generated by the set of allocated DTexecution units. In addition, the intermediate result informationindicates a scratch pad memory for the task and where the correspondingintermediate results are to be stored. For example, for intermediateresult R1-1 (the intermediate result of task 1_1), DST unit 1 isresponsible for overseeing execution of the task 1_1 and coordinatesstorage of the intermediate result as encoded intermediate result slicesstored in memory of DST execution units 1-5. In general, the scratch padis for storing non-DS encoded intermediate results and the intermediateresult storage is for storing DS encoded intermediate results.

FIGS. 33-38 are schematic block diagrams of the distributed storage andtask network (DSTN) module performing the example of FIG. 30. In FIG.33, the DSTN module accesses the data 92 and partitions it into aplurality of partitions 1-z in accordance with distributed storage andtask network (DST) allocation information. For each data partition, theDSTN identifies a set of its DT (distributed task) execution modules 90to perform the task (e.g., identify non-words (i.e., not in a referencedictionary) within the data partition) in accordance with the DSTallocation information. From data partition to data partition, the setof DT execution modules 90 may be the same, different, or a combinationthereof (e.g., some data partitions use the same set while other datapartitions use different sets).

For the first data partition, the first set of DT execution modules(e.g., 1_1, 2_1, 3_1, 4_1, and 5_1 per the DST allocation information ofFIG. 32) executes task 1_1 to produce a first partial result 102 ofnon-words found in the first data partition. The second set of DTexecution modules (e.g., 1_1, 2_1, 3_1, 4_1, and 5_1 per the DSTallocation information of FIG. 32) executes task 1_1 to produce a secondpartial result 102 of non-words found in the second data partition. Thesets of DT execution modules (as per the DST allocation information)perform task 1_1 on the data partitions until the “z” set of DTexecution modules performs task 1_1 on the “zth” data partition toproduce a “zth” partial result 102 of non-words found in the “zth” datapartition.

As indicated in the DST allocation information of FIG. 32, DST executionunit 1 is assigned to process the first through “zth” partial results toproduce the first intermediate result (R1-1), which is a list ofnon-words found in the data. For instance, each set of DT executionmodules 90 stores its respective partial result in the scratchpad memoryof DST execution unit 1 (which is identified in the DST allocation ormay be determined by DST execution unit 1). A processing module of DSTexecution 1 is engaged to aggregate the first through “zth” partialresults to produce the first intermediate result (e.g., R1_1). Theprocessing module stores the first intermediate result as non-DS errorencoded data in the scratchpad memory or in another section of memory ofDST execution unit 1.

DST execution unit 1 engages its DST client module to slice groupingbased DS error encode the first intermediate result (e.g., the list ofnon-words). To begin the encoding, the DST client module determineswhether the list of non-words is of a sufficient size to partition(e.g., greater than a Terabyte). If yes, it partitions the firstintermediate result (R1-1) into a plurality of partitions (e.g., R1-1_1through R1-1 _(—) m). If the first intermediate result is not ofsufficient size to partition, it is not partitioned.

For each partition of the first intermediate result, or for the firstintermediate result, the DST client module uses the DS error encodingparameters of the data (e.g., DS parameters of data 2, which includes3/5 decode threshold/pillar width ratio) to produce slice groupings. Theslice groupings are stored in the intermediate result memory (e.g.,allocated memory in the memories of DST execution units 1-5).

In FIG. 34, the DSTN module is performing task 1_2 (e.g., find uniquewords) on the data 92. To begin, the DSTN module accesses the data 92and partitions it into a plurality of partitions 1-z in accordance withthe DST allocation information or it may use the data partitions of task1_1 if the partitioning is the same. For each data partition, the DSTNidentifies a set of its DT execution modules to perform task 1_2 inaccordance with the DST allocation information. From data partition todata partition, the set of DT execution modules may be the same,different, or a combination thereof. For the data partitions, theallocated set of DT execution modules executes task 1_2 to produce apartial results (e.g., 1^(st) through “zth”) of unique words found inthe data partitions.

As indicated in the DST allocation information of FIG. 32, DST executionunit 1 is assigned to process the first through “zth” partial results102 of task 1_2 to produce the second intermediate result (R1-2), whichis a list of unique words found in the data 92. The processing module ofDST execution 1 is engaged to aggregate the first through “zth” partialresults of unique words to produce the second intermediate result. Theprocessing module stores the second intermediate result as non-DS errorencoded data in the scratchpad memory or in another section of memory ofDST execution unit 1.

DST execution unit 1 engages its DST client module to slice groupingbased DS error encode the second intermediate result (e.g., the list ofnon-words). To begin the encoding, the DST client module determineswhether the list of unique words is of a sufficient size to partition(e.g., greater than a Terabyte). If yes, it partitions the secondintermediate result (R1-2) into a plurality of partitions (e.g., R1-2_1through R1-2 _(—) m). If the second intermediate result is not ofsufficient size to partition, it is not partitioned.

For each partition of the second intermediate result, or for the secondintermediate results, the DST client module uses the DS error encodingparameters of the data (e.g., DS parameters of data 2, which includes3/5 decode threshold/pillar width ratio) to produce slice groupings. Theslice groupings are stored in the intermediate result memory (e.g.,allocated memory in the memories of DST execution units 1-5).

In FIG. 35, the DSTN module is performing task 1_3 (e.g., translate) onthe data 92. To begin, the DSTN module accesses the data 92 andpartitions it into a plurality of partitions 1-z in accordance with theDST allocation information or it may use the data partitions of task 1_1if the partitioning is the same. For each data partition, the DSTNidentifies a set of its DT execution modules to perform task 1_3 inaccordance with the DST allocation information (e.g., DT executionmodules 1_1, 2_1, 3_1, 4_1, and 5_1 translate data partitions 2_1through 2_4 and DT execution modules 1_2, 2_2, 3_2, 4_2, and 5_2translate data partitions 2_5 through 2 _(—) z). For the datapartitions, the allocated set of DT execution modules 90 executes task1_3 to produce partial results 102 (e.g., 1^(st) through “zth”) oftranslated data.

As indicated in the DST allocation information of FIG. 32, DST executionunit 2 is assigned to process the first through “zth” partial results oftask 1_3 to produce the third intermediate result (R1-3), which istranslated data. The processing module of DST execution 2 is engaged toaggregate the first through “zth” partial results of translated data toproduce the third intermediate result. The processing module stores thethird intermediate result as non-DS error encoded data in the scratchpadmemory or in another section of memory of DST execution unit 2.

DST execution unit 2 engages its DST client module to slice groupingbased DS error encode the third intermediate result (e.g., translateddata). To begin the encoding, the DST client module partitions the thirdintermediate result (R1-3) into a plurality of partitions (e.g., R1-3_1through R1-3 _(—) y). For each partition of the third intermediateresult, the DST client module uses the DS error encoding parameters ofthe data (e.g., DS parameters of data 2, which includes 3/5 decodethreshold/pillar width ratio) to produce slice groupings. The slicegroupings are stored in the intermediate result memory (e.g., allocatedmemory in the memories of DST execution units 2-6 per the DST allocationinformation).

As is further shown in FIG. 35, the DSTN module is performing task 1_4(e.g., retranslate) on the translated data of the third intermediateresult. To begin, the DSTN module accesses the translated data (from thescratchpad memory or from the intermediate result memory and decodes it)and partitions it into a plurality of partitions in accordance with theDST allocation information. For each partition of the third intermediateresult, the DSTN identifies a set of its DT execution modules 90 toperform task 1_4 in accordance with the DST allocation information(e.g., DT execution modules 1_1, 2_1, 3_1, 4_1, and 5_1 are allocated totranslate back partitions R1-3_1 through R1-3_4 and DT execution modules1_2, 2_2, 6_1, 7_1, and 7_2 are allocated to translate back partitionsR1-3_5 through R1-3 _(—) z). For the partitions, the allocated set of DTexecution modules executes task 1_4 to produce partial results 102(e.g., 1st through “zth”) of re-translated data.

As indicated in the DST allocation information of FIG. 32, DST executionunit 3 is assigned to process the first through “zth” partial results oftask 1_4 to produce the fourth intermediate result (R1-4), which isretranslated data. The processing module of DST execution 3 is engagedto aggregate the first through “zth” partial results of retranslateddata to produce the fourth intermediate result. The processing modulestores the fourth intermediate result as non-DS error encoded data inthe scratchpad memory or in another section of memory of DST executionunit 3.

DST execution unit 3 engages its DST client module to slice groupingbased DS error encode the fourth intermediate result (e.g., retranslateddata). To begin the encoding, the DST client module partitions thefourth intermediate result (R1-4) into a plurality of partitions (e.g.,R1-4_1 through R1-4 _(—) z). For each partition of the fourthintermediate result, the DST client module uses the DS error encodingparameters of the data (e.g., DS parameters of data 2, which includes3/5 decode threshold/pillar width ratio) to produce slice groupings. Theslice groupings are stored in the intermediate result memory (e.g.,allocated memory in the memories of DST execution units 3-7 per the DSTallocation information).

In FIG. 36, a distributed storage and task network (DSTN) module isperforming task 1_5 (e.g., compare) on data 92 and retranslated data ofFIG. 35. To begin, the DSTN module accesses the data 92 and partitionsit into a plurality of partitions in accordance with the DST allocationinformation or it may use the data partitions of task 1_1 if thepartitioning is the same. The DSTN module also accesses the retranslateddata from the scratchpad memory, or from the intermediate result memoryand decodes it, and partitions it into a plurality of partitions inaccordance with the DST allocation information. The number of partitionsof the retranslated data corresponds to the number of partitions of thedata.

For each pair of partitions (e.g., data partition 1 and retranslateddata partition 1), the DSTN identifies a set of its DT execution modules90 to perform task 1_5 in accordance with the DST allocation information(e.g., DT execution modules 1_1, 2_1, 3_1, 4_1, and 5_1). For each pairof partitions, the allocated set of DT execution modules executes task1_5 to produce partial results 102 (e.g., 1^(st) through “zth”) of alist of incorrectly translated words and/or phrases.

As indicated in the DST allocation information of FIG. 32, DST executionunit 1 is assigned to process the first through “zth” partial results oftask 1_5 to produce the fifth intermediate result (R1-5), which is thelist of incorrectly translated words and/or phrases. In particular, theprocessing module of DST execution 1 is engaged to aggregate the firstthrough “zth” partial results of the list of incorrectly translatedwords and/or phrases to produce the fifth intermediate result. Theprocessing module stores the fifth intermediate result as non-DS errorencoded data in the scratchpad memory or in another section of memory ofDST execution unit 1.

DST execution unit 1 engages its DST client module to slice groupingbased DS error encode the fifth intermediate result. To begin theencoding, the DST client module partitions the fifth intermediate result(R1-5) into a plurality of partitions (e.g., R1-5_1 through R1-5 _(—)z). For each partition of the fifth intermediate result, the DST clientmodule uses the DS error encoding parameters of the data (e.g., DSparameters of data 2, which includes 3/5 decode threshold/pillar widthratio) to produce slice groupings. The slice groupings are stored in theintermediate result memory (e.g., allocated memory in the memories ofDST execution units 1-5 per the DST allocation information).

As is further shown in FIG. 36, the DSTN module is performing task 1_6(e.g., translation errors due to non-words) on the list of incorrectlytranslated words and/or phrases (e.g., the fifth intermediate resultR1-5) and the list of non-words (e.g., the first intermediate resultR1-1). To begin, the DSTN module accesses the lists and partitions theminto a corresponding number of partitions.

For each pair of partitions (e.g., partition R1-1_1 and partitionR1-5_1), the DSTN identifies a set of its DT execution modules 90 toperform task 1_6 in accordance with the DST allocation information(e.g., DT execution modules 1_1, 2_1, 3_1, 4_1, and 5_1). For each pairof partitions, the allocated set of DT execution modules executes task1_6 to produce partial results 102 (e.g., 1^(st) through “zth”) of alist of incorrectly translated words and/or phrases due to non-words.

As indicated in the DST allocation information of FIG. 32, DST executionunit 2 is assigned to process the first through “zth” partial results oftask 1_6 to produce the sixth intermediate result (R1-6), which is thelist of incorrectly translated words and/or phrases due to non-words. Inparticular, the processing module of DST execution 2 is engaged toaggregate the first through “zth” partial results of the list ofincorrectly translated words and/or phrases due to non-words to producethe sixth intermediate result. The processing module stores the sixthintermediate result as non-DS error encoded data in the scratchpadmemory or in another section of memory of DST execution unit 2.

DST execution unit 2 engages its DST client module to slice groupingbased DS error encode the sixth intermediate result. To begin theencoding, the DST client module partitions the sixth intermediate result(R1-6) into a plurality of partitions (e.g., R1-6_1 through R1-6 _(—)z). For each partition of the sixth intermediate result, the DST clientmodule uses the DS error encoding parameters of the data (e.g., DSparameters of data 2, which includes 3/5 decode threshold/pillar widthratio) to produce slice groupings. The slice groupings are stored in theintermediate result memory (e.g., allocated memory in the memories ofDST execution units 2-6 per the DST allocation information).

As is still further shown in FIG. 36, the DSTN module is performing task1_7 (e.g., correctly translated words and/or phrases) on the list ofincorrectly translated words and/or phrases (e.g., the fifthintermediate result R1-5) and the list of unique words (e.g., the secondintermediate result R1-2). To begin, the DSTN module accesses the listsand partitions them into a corresponding number of partitions.

For each pair of partitions (e.g., partition R1-2_1 and partitionR1-5_1), the DSTN identifies a set of its DT execution modules 90 toperform task 1_7 in accordance with the DST allocation information(e.g., DT execution modules 1_2, 2_2, 3_2, 4_2, and 5_2). For each pairof partitions, the allocated set of DT execution modules executes task1_7 to produce partial results 102 (e.g., 1^(st) through “zth”) of alist of correctly translated words and/or phrases.

As indicated in the DST allocation information of FIG. 32, DST executionunit 3 is assigned to process the first through “zth” partial results oftask 1_7 to produce the seventh intermediate result (R1-7), which is thelist of correctly translated words and/or phrases. In particular, theprocessing module of DST execution 3 is engaged to aggregate the firstthrough “zth” partial results of the list of correctly translated wordsand/or phrases to produce the seventh intermediate result. Theprocessing module stores the seventh intermediate result as non-DS errorencoded data in the scratchpad memory or in another section of memory ofDST execution unit 3.

DST execution unit 3 engages its DST client module to slice groupingbased DS error encode the seventh intermediate result. To begin theencoding, the DST client module partitions the seventh intermediateresult (R1-7) into a plurality of partitions (e.g., R1-7_1 through R1-7_(—) z). For each partition of the seventh intermediate result, the DSTclient module uses the DS error encoding parameters of the data (e.g.,DS parameters of data 2, which includes 3/5 decode threshold/pillarwidth ratio) to produce slice groupings. The slice groupings are storedin the intermediate result memory (e.g., allocated memory in thememories of DST execution units 3-7 per the DST allocation information).

In FIG. 37, the distributed storage and task network (DSTN) module isperforming task 2 (e.g., find specific words and/or phrases) on the data92. To begin, the DSTN module accesses the data and partitions it into aplurality of partitions 1-z in accordance with the DST allocationinformation or it may use the data partitions of task 1_1 if thepartitioning is the same. For each data partition, the DSTN identifies aset of its DT execution modules 90 to perform task 2 in accordance withthe DST allocation information. From data partition to data partition,the set of DT execution modules may be the same, different, or acombination thereof. For the data partitions, the allocated set of DTexecution modules executes task 2 to produce partial results 102 (e.g.,1^(st) through “zth”) of specific words and/or phrases found in the datapartitions.

As indicated in the DST allocation information of FIG. 32, DST executionunit 7 is assigned to process the first through “zth” partial results oftask 2 to produce task 2 intermediate result (R2), which is a list ofspecific words and/or phrases found in the data. The processing moduleof DST execution 7 is engaged to aggregate the first through “zth”partial results of specific words and/or phrases to produce the task 2intermediate result. The processing module stores the task 2intermediate result as non-DS error encoded data in the scratchpadmemory or in another section of memory of DST execution unit 7.

DST execution unit 7 engages its DST client module to slice groupingbased DS error encode the task 2 intermediate result. To begin theencoding, the DST client module determines whether the list of specificwords and/or phrases is of a sufficient size to partition (e.g., greaterthan a Terabyte). If yes, it partitions the task 2 intermediate result(R2) into a plurality of partitions (e.g., R2_1 through R2 _(—) m). Ifthe task 2 intermediate result is not of sufficient size to partition,it is not partitioned.

For each partition of the task 2 intermediate result, or for the task 2intermediate results, the DST client module uses the DS error encodingparameters of the data (e.g., DS parameters of data 2, which includes3/5 decode threshold/pillar width ratio) to produce slice groupings. Theslice groupings are stored in the intermediate result memory (e.g.,allocated memory in the memories of DST execution units 1-4, and 7).

In FIG. 38, the distributed storage and task network (DSTN) module isperforming task 3 (e.g., find specific translated words and/or phrases)on the translated data (R1-3). To begin, the DSTN module accesses thetranslated data (from the scratchpad memory or from the intermediateresult memory and decodes it) and partitions it into a plurality ofpartitions in accordance with the DST allocation information. For eachpartition, the DSTN identifies a set of its DT execution modules toperform task 3 in accordance with the DST allocation information. Frompartition to partition, the set of DT execution modules may be the same,different, or a combination thereof. For the partitions, the allocatedset of DT execution modules 90 executes task 3 to produce partialresults 102 (e.g., 1^(st) through “zth”) of specific translated wordsand/or phrases found in the data partitions.

As indicated in the DST allocation information of FIG. 32, DST executionunit 5 is assigned to process the first through “zth” partial results oftask 3 to produce task 3 intermediate result (R3), which is a list ofspecific translated words and/or phrases found in the translated data.In particular, the processing module of DST execution 5 is engaged toaggregate the first through “zth” partial results of specific translatedwords and/or phrases to produce the task 3 intermediate result. Theprocessing module stores the task 3 intermediate result as non-DS errorencoded data in the scratchpad memory or in another section of memory ofDST execution unit 7.

DST execution unit 5 engages its DST client module to slice groupingbased DS error encode the task 3 intermediate result. To begin theencoding, the DST client module determines whether the list of specifictranslated words and/or phrases is of a sufficient size to partition(e.g., greater than a Terabyte). If yes, it partitions the task 3intermediate result (R3) into a plurality of partitions (e.g., R3_1through R3 _(—) m). If the task 3 intermediate result is not ofsufficient size to partition, it is not partitioned.

For each partition of the task 3 intermediate result, or for the task 3intermediate results, the DST client module uses the DS error encodingparameters of the data (e.g., DS parameters of data 2, which includes3/5 decode threshold/pillar width ratio) to produce slice groupings. Theslice groupings are stored in the intermediate result memory (e.g.,allocated memory in the memories of DST execution units 1-4, 5, and 7).

FIG. 39 is a diagram of an example of combining result information intofinal results 104 for the example of FIG. 30. In this example, theresult information includes the list of specific words and/or phrasesfound in the data (task 2 intermediate result), the list of specifictranslated words and/or phrases found in the data (task 3 intermediateresult), the list of non-words found in the data (task 1 firstintermediate result R1-1), the list of unique words found in the data(task 1 second intermediate result R1-2), the list of translation errorsdue to non-words (task 1 sixth intermediate result R1-6), and the listof correctly translated words and/or phrases (task 1 seventhintermediate result R1-7). The task distribution module provides theresult information to the requesting DST client module as the results104.

FIG. 40A is a schematic block diagram of an embodiment of a dispersedstorage network (DSN) that includes the distributed storage and task(DST) client module 34 of FIG. 1, the network 24 of FIG. 1, and aplurality of storage generations including storage generations 1-5. TheDST client module 34 includes a deterministic function module 350. Thedeterministic function module 350 may be implemented utilizing theprocessing module 84 of FIG. 3. Each storage generation includes a setof DST execution (EX) units 1-n. Each DST execution unit may beimplemented utilizing the DST execution unit 36 of FIG. 1.

The DSN functions to retrieve multi-generational stored data from theplurality of storage generations. In an example of operation of theretrieving of the multi-generational stored data, the DST client module34 receives an access request 352 associated with a data object. Theaccess request 352 includes one or more of a data object name (e.g.,foo), a request type indicator (e.g., read, write, delete, update, list;i.e. a retrieval request), and a requesting entity identifier (ID).Having received the access request 352, the DST client module 34 obtainsa vault identifier (ID) associated with the access request 352. Theobtaining includes at least one of performing a lookup using the dataobject name and identifying an affiliation between the access requestand the vault ID (e.g., a relationship between the requesting entity IDand the vault ID). For example, the DST client module 34 accesses systemregistry information using the requesting entity ID to look up the vaultID.

Having obtained the vault ID, the DST client module 34 generates, basedon the data object name, a first retrieval request for retrievingmetadata addressing information, where the first retrieval request isformatted in accordance with a read request format of the DSN (e.g.,read slice requests 354). The generating includes generating a set offirst level read requests (e.g., retrieval requests 1) for retrieving atleast a decode threshold number of metadata addressing informationslices, where the metadata addressing information includes addressinginformation regarding storage of metadata (e.g., a storage generationidentifier) within the DSN, where the metadata addressing informationwas dispersed storage error encoded to produce a set of metadataaddressing information slices, and where the decode threshold number ofmetadata addressing information slices represents a minimum number ofmetadata addressing information slices of the set of metadata addressinginformation slices that is required to recover the metadata addressinginformation. The generating further includes identifying a storagegeneration of the plurality of storage generations based on the accessrequest 352. For example, the deterministic function module 350 performsa deterministic function on the data object name of the access request352 to produce at least a portion of a DSN address associated with theset of first level read requests (e.g., identifying which fixedgeneration of the plurality of generations, i.e. generation 4). Thedeterministic function includes at least one of a hash based messageauthentication code, a hashing function, a mask generating function, anda sponge function. The operation of the deterministic function module350 is discussed in greater detail with reference to FIG. 40B.

Having generated the set of first level read requests of the firstretrieval request, the DST client module 34 sends, via the network 24,the retrieval requests 1 to the DST execution units of the storagegeneration 4 (e.g., the identified fixed generation associated with thedata object name), receives read slice responses 356 that includesretrieval responses 1, and extracts the at least a decode thresholdnumber of metadata addressing information slices from the read sliceresponses 356. Having produced the at least a decode threshold number ofmetadata addressing information slices, the DST client module 34dispersed storage error decodes the least a decode threshold number ofmetadata addressing information slices to recover the metadataaddressing information. Having recovered the metadata addressinginformation, the DST client module 34 extracts the addressinginformation regarding the storage of the metadata. For instance, the DSTclient module 34 extracts the addressing information regarding thestorage of the metadata to identify the storage generation 2 (e.g., themetadata was previously stored in the storage generation 2).

Having retrieved the metadata addressing information, the DST clientmodule 34 generates, based on the retrieved metadata addressinginformation, a second retrieval request for retrieving metadata (e.g.,of the data object), where the second retrieval request is formatted inaccordance with the read request format of the DSN. The metadataincludes one or more of addressing information regarding storage of aplurality of sets of encoded data slices of the data object within theDSN (e.g., a source name of the data object, a plurality of sets ofslice names of the data object, a virtual DSN address associated withstorage of the data object), a data size indicator, a data typeindicator, a data priority indicator, a data owner identifier, a datarecipient identifier, an access control list of the data, a timestamp,the data object name, the vault identifier, a DSN address of adirectory, a DSN address of an index node of a dispersed hierarchicalindex, a generation pointer DSN address (e.g., the DSN addressassociated with the set of first level read requests), and any otherinformation that is associated with the data object.

The generating the second retrieval includes generating, based on themetadata addressing information, a set of second level read requests(e.g., retrieval request 2) for retrieving at least a decode thresholdnumber of metadata slices (e.g., a same or different decode thresholdnumber as the decode threshold number of metadata addressing informationslices), where the metadata includes the addressing informationregarding the storage of the plurality of sets of encoded data slices ofthe data object within the DSN, where the metadata was dispersed storageerror encoded to produce a set of metadata slices, and where the decodethreshold number of metadata slices represents a minimum number ofmetadata slices of the set of metadata slices that is required torecover the metadata.

Having generated the set of second level requests of the secondretrieval request, the DST client module 34 sends, via the network 24,the retrieval requests 2 to the DST execution units of the storagegeneration 2 (e.g., as indicated by the metadata addressinginformation), receives further read slice response 356 that includesretrieval responses 2, and extracts the at least a decode thresholdnumber of metadata slices from the further read slice responses 356.Having produced the at least a decode threshold number of metadataslices, the DST client module 34 dispersed storage error decodes the atleast a decode threshold number of metadata slices to recover themetadata as retrieved metadata.

Having recovered the metadata, the DST client module 34 generates, basedon the retrieved metadata, a third retrieval request for retrieving atleast a portion of the data object associated with the data object name,wherein the third retrieval request is formatted in accordance with theread request format of the DSN. The generating the third retrievalrequest includes generating, based on the retrieved metadata, at leastone set of third level read requests (e.g., retrieval request 3) forretrieving at least a decode threshold number of encoded data slices(e.g., a same or different decode threshold number as the decodethreshold number is associated with the metadata addressing informationand the metadata), where the data object was dispersed storage errorencoded to produce a plurality of sets of encoded data slices that werestored in a corresponding storage generation, and where the decodethreshold number of encoded data slices represents a minimum number ofencoded data slices of a set of the plurality of sets of encoded dataslices that is required to recover the portion of the data object.

Having generated the at least one set of third level read requests, theDST client module 34 sends, via the network 24, the retrieval requests 3to the DST execution units of the storage generation 5 (e.g., asindicated by the metadata), receives still further read slice responses356 that includes retrieval responses 3, and for each set of encodeddata slices, extracts the at least a decode threshold number of encodeddata slices from the still further read slice responses 356. Havingproduced, for each set of encoded data slices, the at least a decodethreshold number of encoded data slices, the DST client module 34dispersed storage error decodes, for each set of encoded data slices,the at least a decode threshold number of encoded data slices to recoverthe data object as a recovered data object. Having recovered the dataobject, the DST client module 34 issues an access response 358 thatincludes the recovered data object.

FIG. 40B is a schematic block diagram illustrating an embodiment of thedeterministic function module 350 of FIG. 40A utilized to retrieve data.As a still further example of operation of the retrieving of themulti-generational stored data as discussed with reference to FIG. 40A,the deterministic function module 350 performs the deterministicfunction on the data object name of the access request 352 to produce adigital value that includes generation pointer source name information360. For example, the deterministic function module 350 performs a maskgenerating function on a data object name of foo to produce the digitalvalue.

Having performed the deterministic function, the deterministic functionmodule 350 (e.g., or hereafter, any other processing module) uses afirst portion of the digital value as a generation identifier of theread request format of the DSN and uses a second portion of the digitalvalue as an object identifier of the read request format of the DSN. Forexample, the deterministic function module 350 uses the first portion asa generation identifier (ID) 4 and the second portion as an object ID5E8.

Having identified the generation ID and object ID, the deterministicfunction module 350 generates the first retrieval request by determininga vault identifier associated with the data object. For example, thedeterministic function module 350 performs a system registry lookuputilizing an identifier of a requesting entity to identify a vault ID of457. Having identified the vault ID, the deterministic function module350 uses the vault identifier in a vault identifier field of the readrequest format of the DSN. For example, the deterministic functionmodule 350 generates a source name for a foo metadata generation pointer362 to include the vault ID of 457, the generation ID 4, and the objectID of 5E8; and generates the first retrieval request to include the foometadata generation pointer 362.

Having generated the first retrieval request, the deterministic functionmodule 350 accesses the DSN by sending the first retrieval request tothe storage generation 4, receives metadata addressing informationslices of a generation pointer for foo 364, and decodes the receivedmetadata addressing information slices to reproduce metadata addressinginformation 366. The metadata addressing information 366 includes a foometadata object number of CA9 and a foo metadata generation ID 2.

Having reproduced the metadata addressing information 366, thedeterministic function module 350 generates the second retrieval requestby extracting a generation identifier (e.g., generation 2) and an objectidentifier (e.g., CA9) from the metadata addressing information 366.Next, the deterministic function module 350 determines the vaultidentifier associated with the data object. Having determined the vaultID, the deterministic function module 350 generates a source name forfoo metadata 368 of the second retrieval request by using the generationidentifier (e.g., 2) in a generation identifier field of the readrequest format of the DSN, using the object identifier (e.g., CA9) in anobject identifier field of the read request format of the DSN, and usingthe vault identifier (e.g., 457) in a vault identifier field of the readrequest format of the DSN.

Having generated the second retrieval request, the deterministicfunction module 350 accesses the DSN by sending a second retrievalrequest to the storage generation 2, receives metadata slices of a foometadata object 370, and decodes the received metadata slices toreproduce the metadata 372 (e.g., for foo). The metadata for foo 372includes a source name for the foo data object 374.

Having reproduce the metadata for foo 372, the deterministic functionmodule 350 generates the third retrieval request by using fields of thesource name for foo data object 374 (e.g., vault ID 457, generation ID5, object ID B93). Having generated the third retrieval request, thedeterministic function module 350 accesses the DSN by sending the thirdretrieval request to the storage generation 5, receives encoded dataslices of a stored foo data object 376, dispersed storage error decodesthe received encoded data slices to reproduce the data object foo. FIG.40C is a flowchart illustrating an example of retrievingmulti-generational stored data. In particular, a method is presented foruse in conjunction with one or more functions and features described inconjunction with FIGS. 1-39, 40A-B, and also FIG. 40C. The method beginsat step 380 where a processing module of a computing device of one ormore computing devices of a dispersed storage network (DSN) performs adeterministic function on a data object name of a data object forretrieval to produce a digital value. Having produced the digital value,the processing module uses a first portion of the digital value as ageneration identifier (ID) of a read request format of the DSN for afirst retrieval request and uses a second portion of the digital valueas an object identifier of the read request format of the DSN of thefirst retrieval request.

The method continues at step 382 where the processing module determinesa vault identifier associated with the data object. For example, theprocessing module utilizes a requesting entity ID to perform a systemregistry lookup to produce the vault ID. As another example, theprocessing module utilizes the data object name and performs a directorylookup to produce the vault ID. Having produced the vault ID, theprocessing module uses the vault identifier in a vault identifier fieldof the read request format of the DSN of the first retrieval request.

The method continues at step 384 where the processing module generates,based on the data object name, the first retrieval request forretrieving metadata addressing information, where the first retrievalrequest is formatted in accordance with the read request format of theDSN (e.g., the first retrieval request includes the vault ID, thegeneration ID, and the object ID corresponding to a DSN addressassociated with the metadata addressing information). The generating thefirst retrieval request includes generating a set of first level readrequests for retrieving at least a decode threshold number of metadataaddressing information slices, where the metadata addressing informationincludes addressing information regarding storage of the metadata withinthe DSN, where the metadata addressing information was dispersed storageerror encoded to produce a set of metadata addressing informationslices, and where the decode threshold number of metadata addressinginformation slices represents a minimum number of metadata addressinginformation slices of the set of metadata addressing information slicesthat is required to recover the metadata addressing information.

The method continues at step 386 where the processing module decodes theleast a decode threshold number of metadata addressing informationslices to recover the metadata addressing information. For example, theprocessing module sends the first level read requests to storage unitsof the DSN, receives the at least a decode threshold number of metadataaddressing information slices, and dispersed storage error decodes theat least a decode threshold number of metadata addressing informationslices to produce retrieved metadata addressing information.

The method continues at step 388 where the processing module extracts ageneration identifier and an object identifier from the metadataaddressing information. Having extracted the generation ID of the objectID, the processing module uses the generation identifier in a generationidentifier field of the read request format of the DSN for a secondretrieval request and uses the object identifier in an object identifierfield of the read request format of the DSN for the second retrievalrequest. The processing module may further determine the vaultidentifier associated with the data object (e.g., with metadata) and usethe vault identifier in a vault identifier field of the read requestformat of the DSN for the second retrieval request.

The method continues at step 390 where the processing module generates,based on the retrieved metadata addressing information, the secondretrieval request for retrieving metadata, where the second retrievalrequest is formatted in accordance with the read request format of theDSN (e.g., the second retrieval request includes the vault ID of themetadata, the generation ID of the metadata, and the object ID of themetadata corresponding to a DSN address associated with the metadata).The generating the second retrieval request includes generating, basedon the metadata addressing information, a set of second level readrequests for retrieving at least a decode threshold number of metadataslices, where the metadata includes addressing information regardingstorage of a plurality of sets of encoded data slices of the data objectwithin the DSN, where the metadata was dispersed storage error encodedto produce a set of metadata slices, and where the decode thresholdnumber of metadata slices represents a minimum number of metadata slicesof the set of metadata slices that is required to recover the metadata.

The method continues at step 392 where the processing module decodes theat least a decode threshold number of metadata slices to recover themetadata. For example, the processing module sends the second level readrequests to the storage units of the DSN, receives the at least a decodethreshold number of metadata slices, and dispersed storage error decodesthe at least a decode threshold number of metadata slices to produceretrieved metadata.

The method continues at step 394 where the processing module generates,based on the retrieved metadata (e.g., using the addressing informationregarding the storage of the plurality of sets of encoded data slices ofthe data object), a third retrieval request for retrieving at least aportion of the data object associated with the data object name, wherethe third retrieval request is formatted in accordance with the readrequest format of the DSN. The generating includes the processing modulegenerating, based on the metadata, at least one set of third level readrequests for retrieving at least a decode threshold number of encodeddata slices, where the data object was dispersed storage error encodedto produce a plurality of sets of encoded data slices, and where thedecode threshold number of encoded data slices represents a minimumnumber of encoded data slices of a set of the plurality of sets ofencoded data slices that are required to recover the portion of the dataobject. For example, the processing module sends the third level readrequests to the storage units of the DSN, receives the at least a decodethreshold number of encoded data slices for each set of the plurality ofsets of encoded data slices, and dispersed storage error decodes each ofthe at least a decode threshold number of encoded data slices to producea retrieved data object.

The method described above in conjunction with the processing module canalternatively be performed by other modules of the dispersed storagenetwork or by other devices. In addition, at least one memory section(e.g., a computer readable storage medium) that stores operationalinstructions can, when executed by one or more processing modules of oneor more computing devices of the dispersed storage network (DSN), causethe one or more computing devices to perform any or all of the methodsteps described above.

FIG. 41A is a schematic block diagram of another embodiment of adispersed storage network (DSN) that includes two or more distributedstorage and task (DST) client modules 1-2, the network 24 of FIG. 1, anda DST execution (EX) unit set 400. The DST execution unit set 400includes a set of DST execution units 1-n. Each DST execution unit maybe implemented utilizing the DST execution unit 36 of FIG. 1. Each DSTclient module may be implemented utilizing the DST client module 34 ofFIG. 1.

The DSN functions to store a data object in the DST execution unit set400 and to provide confirmation of the storage of the data object in theDST execution unit set. In an example of operation to store the dataobject, the DST client module 1 receives a store data object request 401that includes a data object and an object name of the data object. TheDST client module 1 facilitates storage of the data object in the DSTexecution unit set 400. For example, the DST client module 1 dispersedstorage error encodes the data object to produce a plurality of sets ofencoded data slices, generates a plurality of sets of slice names tocorrespond to the plurality of sets of encoded data slices, generatesone or more sets of write slice requests 402 that includes the pluralityof sets of encoded data slices and the plurality of sets of slice names,sends, via the network 24, the one or more sets of write slice requests402 to the set of DST execution units 1-n.

Having facilitated the storage of the data object in the DST executionunit set, the DST client module 1 applies K unique deterministicfunctions to the object name to produce K deterministic values 1-K,where each deterministic value ranges from 1-M and where M indicates anumber of buckets. Each DST execution unit is associated with a portionof the deterministic range values of 1-M in accordance with a bucketmapping scheme. For example, each DST execution unit is associated withM/n buckets when the bucket mapping scheme includes even distribution.For instance, DST execution unit 1 is associated with a first nth amountof the deterministic range value 1-M, DST execution unit 2 is associatedwith a next and amount of the deterministic range values 1-M, etc.

For each deterministic value 1-K, the DST client module 1 identifies acorresponding DST execution unit of the set of DST execution units basedon the deterministic value and the bucket mapping scheme. Havingidentified the corresponding DST execution unit for each of thedeterministic values, the DST client module 1 issues update bucketrequests 1-K to at least some of the DST execution units in accordancewith the identified corresponding DST execution units. Each bucketrequest includes the corresponding deterministic value of the range 1-M.

The DST execution units (e.g., K or less) receives the update bucketrequests 1-K and updates a value of a locally stored bucket to indicatean active state receiving an update bucket request that corresponds to adeterministic value associated with the bucket. For example, DSTexecution unit 2 receives the update bucket request 1 to update a bucketassociated with a deterministic value of 150,000 when M=1 millionbuckets and n=10 DST execution units (e.g., and each DST execution unitis mapped to 100,000 buckets).

In an example of operation to provide the confirmation of storage of thedata object, the DST client module 2 receives a data object storageconfirmation request 404, where the data object storage confirmationrequest 404 includes the object name of the data object. The DST clientmodule 2 applies the K unique deterministic functions to the receivedobject name to produce the K deterministic values 1-K. For eachdeterministic value, the DST client module 2 identifies thecorresponding DST execution unit in accordance with the bucket mappingscheme.

Having identified each corresponding DST execution unit, the DST clientmodule 2 sends, via the network 24, bucket state requests 1-K to thecorresponding DST execution units, where the bucket state requests 1-Kincludes the deterministic values 1-K. The DST client module 2 receivesbucket state responses 1-K from the DST execution units, where eachbucket state response indicates the state of the bucket (e.g., active,inactive).

Having received the bucket state responses, the DST client module 2determines whether the data object is stored in the DST execution unitset based on the received bucket state responses. As a specific example,the DST client module 2 indicates that the data object is possiblystored when a number of the received bucket state responses thatindicate the active state is greater than or equal to a high thresholdlevel. For instance, the DST client module 2 indicates that the dataobject is possibly stored when the all K responses indicate the activestate and the height threshold level is K. As another specific example,the DST client module 2 indicates that the data object is not storedwhen the number of the received bucket state responses indicates thatindicate the inactive state is greater or equal to a than a lowthreshold level. For instance, the DST client module 2 indicates thatthe data object is not stored when just one of the K responses indicatesthe inactive state and the low threshold level is 1. Having determinedwhether the data object is stored, the DST client module 2 outputs adata object storage confirmation response 406 that includes theindication of possible storage or the indication of non-storage.

FIG. 41B is a flowchart illustrating an example of confirming storage ofa data object. The method begins or continues, when storing data, atstep 410 where a processing module (e.g., of a distributed storage andtask (DST) client module) receives a store data object request thatincludes a data object and an object name of the data object. The methodcontinues at step 412 where the processing module facilitates storingthe data object in a set of storage units using a dispersed storageerror coding function. The method continues at step 414 where theprocessing module applies K unique deterministic functions to the objectname to produce K deterministic values. Each deterministic value fallswithin a range of 1-M.

For each deterministic value, the method continues at step 416 where theprocessing module identifies a corresponding storage unit of the set ofstorage units based on the deterministic value. For example, theprocessing module utilizes a bucket mapping scheme to identify eachstorage unit associated with each deterministic value. The methodcontinues at step 418 where the processing module sends an update bucketrequest to the corresponding storage unit, where the update bucketrequest includes the deterministic value. The method continues at step420 where each storage unit updates a state value of a bucket (e.g., toactive) when receiving an update bucket request that includes thedeterministic value associated with the bucket.

The method continues, when confirming storage of the data, at step 422where the processing module receives a data object storage confirmationrequest. The data object storage confirmation request includes theobject name of the data object. The method continues at step 424 wherethe processing module applies the K unique deterministic functions tothe object name to produce the K deterministic values 1-K.

For each deterministic value, the method continues at step 426 where theprocessing module identifies the corresponding storage unit of the setof storage units based on the deterministic value and the bucket mappingscheme. The method continues at step 428 where the processing modulesends a bucket state request to the corresponding storage unit, wherethe bucket state request includes the deterministic value.

The method continues at step 430 where the processing module receivesbucket state responses from at least some of the storage units, whereeach bucket state response indicates the state value of the bucket. Themethod continues at step 432 where the processing module generates anindication of storage of the data object based on the received bucketstate responses.

FIGS. 42A and 42B are a schematic block diagram of another embodiment ofa dispersed storage network (DSN) that includes the distributed storageand task (DST) processing unit 16 of FIG. 1, a wide area network 440,and a DST execution (EX) unit set 442. The wide area network 440 may beimplemented utilizing a wide area portion of the network 24 of FIG. 1.The DST execution unit set 442 includes a set of DST execution units1-n. At least one DST execution unit includes the DST client module 34of FIG. 1. Each DST execution unit may be implemented utilizing the DSTexecution unit 36 of FIG. 1. Hereafter, each DST execution unit may bereferred to interchangeably as a storage unit of a plurality of storageunits and/or a set of storage units. At least two or more of the DSTexecution units are operably coupled by a local area network 444. Thelocal area network 444 may be implemented utilizing a local area networkportion of the network 24.

The DSN functions to delegate an iterative storage unit access processto provide access to data stored in the DST execution unit set 442. Theiterative storage unit access process includes one or more processingmodules (e.g., of the DST processing unit 16, of the DST client module34) performing one or more data storage address determination steps toproduce addressing information with regards to the data to enable accessto the data utilizing the addressing information.

The one or more data storage address determination steps includesiteratively accessing an addressing information structure utilizinginformation associated with the data to produce the addressinginformation. The addressing information structure includes at least oneof a DSN directory (e.g., a flat list), utilization of a deterministicfunction (e.g., performing the deterministic function on the informationassociated with the data to produce at least a portion of the addressinginformation), and a dispersed hierarchical index (e.g., an index tree).The dispersed article index includes a tree index structure utilizing aplurality of levels where a top-level includes a root node for entryinto the index for searches, a series of intermediate levels includingindex nodes that include index key references pointing to other nodes ofthe tree (e.g., iteratively searched utilizing index keys as theinformation associated with the data, and a lowest level of leaf nodes,where each leaf node includes an association of a search index key and aDSN address associated with the data storage. For example, a dispersedhierarchical index associated with the data is stored as a plurality ofindex nodes in the DST execution unit set 442, where each index node isdispersed storage error encoded to produce a set of index slices thatare stored in the set of DST execution units 1-n. As such, one or moreof the DST processing unit 16 and the DST client module 34 accesses oneor more of the index nodes by accessing the stored index slices from theDST execution unit set 442. For instance, the DST client module 34accesses five index nodes of the dispersed article index by iterativelyrecovering five index node objects from the set of DST execution units1-n to ultimately produce the DSN address associated with the data toenable recovery of the data.

FIG. 42A illustrates steps of an example of operation of the delegatingof the iterative storage unit access process where the DST processingunit 16 receives a DSN access request 446 from a requesting entity toaccess the data. The accessing includes at least one of storing thedata, retrieving the data, listing the data, and deleting the data. TheDSN access request 446 includes at least one of a request for theaddressing information regarding data having one or more search criteria(e.g., index keys), where the iterative storage unit access process isexecuted to traverse the index tree to identify the data based on theone or more search criteria, and a request for the data having the oneor more search criteria.

Having received the DSN access request 446, the DST processing unit 16determines whether the DSN access request 446 involves the iterativestorage unit access process. For example, the DST processing unit 16indicates that the DSN access request 446 involves the iterative storageunit access process when the DSN access request 446 includes the searchcriteria.

When the DSN access request 446 involves the iterative storage unitaccess process, the DST processing unit 16 determines, based onconfiguration of the plurality of storage units storing data objectsassociated with the DSN access request 446, that a storage unit of theplurality of storage units is capable of executing at least a portion ofthe iterative storage unit access process better than the DST processingunit 16 (e.g., a computing device). For example, the DST processing unit16 indicates that the DST execution unit 1 is capable of executing theat least a portion of the iterative storage in the process better thanthe DST processing unit 16 when the DST processing unit 16 determinesthat the DST execution unit 1 is capable of executing the at least aportion of the iterative storage unit access process better than the DSTprocessing unit 16 when the DST execution unit 1 is coupled to a desirednumber (e.g., a decode threshold number minus 1, where a decodethreshold number per set of encoded data slices is required forrecovery) of other DST execution units of the plurality of DST executionunits via the LAN connection 444.

As another example, the DST processing unit 16 indicates that the DSTexecution unit 1 is capable of executing the at least a portion of theiterative storage unit access process better than the DST processingunit 16 when the DST processing unit 16 determines that the DSTexecution unit 1 is coupled via the local area network (LAN) 444connection to one or more other DST execution units of the plurality ofDST execution units (e.g., storage units) and the DST processing unit 16determines that a reduction in wide area network (WAN) communications(e.g., via the wide area network 440) constitutes better execution ofthe at least a portion of the iterative storage unit access process(e.g., more efficient to access the index nodes of the index tree viathe land 444 than over the wide area network 440). The reduction in WANcommunications includes at least one of a reduction in WAN traffic and areduction in latency of processing the at least a portion of theiterative storage unit access process.

Having identified the DST execution unit (e.g., DST execution unit 1)that is capable of executing the at least a portion of the iterativestorage unit access process better than the DST processing unit 16, theDST processing unit 16 sends, via the wide area network 440 (e.g., whencoupled via the wide area network 440), the DSN access request 446 and acontrol command 448 to the storage unit (e.g., DST execution unit 1),where the control command 448 instructs the storage unit to perform atleast a portion of the iterative storage unit access process. Thecontrol command 448 includes one or more of an instruction indicating adecode threshold number of storage units of the plurality of storageunits to access while executing the at least a portion of the iterativestorage unit access process, where at least one of the decode thresholdnumber of storage units is coupled via a WAN connection to the storageunit, instructions to perform the iterative storage unit access process(e.g., the search criteria), and to provide a complete response (e.g.,include the data) to the DSN access request.

Alternatively, or in addition to, the DST processing unit 16 sends, viathe wide area network 440, the DSN access request 446 and anothercontrol command 448 to one or more storage units of a second sub-set ofthe plurality of storage units when the processing module sends the DSNaccess request 446 and the control command 448 to the storage unit whenthe storage unit represents a sub-set of the plurality of storage unitsto subsequently provide a collective response. For instance, the DSTprocessing unit 16 sends the other control command 448 to the DSTexecution unit n when the DST execution unit n is required for theiterative storage unit access process but is not operably coupled to theDST execution unit 1 via the LAN 444.

FIG. 42B illustrates further steps of the example of operation of thedelegating of the iterative storage unit access process where the DSTprocessing unit 16 receives, via the wide area network 440 from the DSTexecution unit 1, at least a partial response 452 to the DSN accessrequest 446. The partial response 452 includes at least one of acomplete response that includes the recovered data, the addressinginformation regarding the data, and a group iteration partial responsefrom the DST execution unit 1 that represents the collective response ofthe sub-set of the plurality of storage units. For example, the DSTclient module 34 performs slices accesses 450, via the LAN 444, torecover a decode threshold number of index slices for each index node inaccordance with the iterative storage unit access process from a decodethreshold number of DST execution units to identify the addressinginformation of the data, retrieves at least a decode threshold number ofencoded data slices for each set of a plurality of encoded data slicesof the data from the decode threshold number of DST execution units, foreach set of encoded data slices, dispersed storage error decodes theretrieved decode threshold number of encoded data slices to reproducethe data, and issues, via the wide area network 440, the partialresponse 452 to the DST processing unit 16, where the partial response452 includes the reproduced data. Having received the reproduced data,the DST processing unit 16 issues a DSN access response 454 to therequesting entity, where the DSN access response 454 includes thereproduced data.

Alternatively, or in addition to, for each iteration of the iterativestorage unit access process, while receiving a group iteration partialresponse from the DST execution unit 1 that represents a collectiveresponse of a sub-set of the plurality of storage units, the DSTprocessing unit 16 receives iterative partial responses from one or moreDST execution units of the second sub-set of the plurality of storageunits (e.g., an iterative partial response 456 from the DST executionunit n) and processes the group iterative partial response 456 and theiterative partial response 452 to produce the DSN access response 454that includes an iterative response (e.g., the recovered data).

FIG. 42C is a flowchart illustrating an example of delegating aniterative storage unit access process. In particular, a method ispresented for use in conjunction with one or more functions and featuresdescribed in conjunction with FIGS. 1-39, 42A-B, and also FIG. 42C. Themethod begins at step 460 where a processing module of a computingdevice of one or more computing devices of a dispersed storage network(DSN) determines whether a DSN access request involves an iterativestorage unit access process. For example, the processing moduleindicates that the DSN access request involves the iterative storageunit process when receiving search criteria for data to be retrieved.

When the DSN access request involves the iterative storage unit accessprocess, the method continues at step 462 where the processing unitdetermines, based on configuration of a plurality of storage unitsstoring data objects associated with the DSN access request, that astorage unit of the plurality of storage units is capable of executingat least a portion of the iterative storage unit access process betterthan the computing device. For example, the processing module indicatesthat the storage unit is capable of executing the at least a portion ofthe iterative storage unit access process better than the computingdevice (e.g., associated with the processing module) when the storageunit is coupled to a desired number of other storage units (e.g., adecode threshold number in total) of the plurality of storage units viaa LAN connection. As another example, the processing module indicatesthat the storage unit is capable of executing the at least a portion ofthe iterative storage unit process better than the computing device whenthe processing module determines that the storage unit is coupled via alocal area network (LAN) connection to one or more other storage unitsof the plurality of storage units and the processing module determinesthat a reduction in wide area network (WAN) communications constitutesbetter execution of the at least a portion of the iterative storage unitaccess process.

The method continues at step 464 where the processing module sends theDSN access request and a control command to the storage unit, where thecontrol command instructs the storage unit to perform at least a portionof the iterative storage unit access process. The control commandincludes one or more of an instruction indicating a decode thresholdnumber of storage units of the plurality of storage units to accesswhile executing the at least a portion of the iterative storage unitaccess process, where at least one of the decode threshold number ofstorage units is coupled via a WAN connection to the storage unit, andinstructions to perform the iterative storage unit access process and toprovide a complete response to the DSN access request. Alternatively, orin addition to, the processing module sends the DSN access request andanother control command to storage units of a second sub-set of theplurality of storage units when the processing module sends the DSNaccess request and the control command to the storage unit when thestorage unit represents a sub-set of the plurality of storage units tosubsequently provide a collective response (e.g., the recovered data).

The method continues at step 466 where the processing module receives,from the storage unit, at least a partial response to the DSN accessrequest. The partial response includes at least one of a completeresponse that includes the recovered data, the addressing informationregarding the data, and a group iteration partial response from thestorage unit that represents the collective response of the sub-set ofthe plurality of storage units. When the other control command isutilized, for each iteration of the iterative storage unit accessprocess, the method continues at step 468, while receiving a groupiteration partial response from the storage unit that represents acollective response of a sub-set of the plurality of storage units, theprocessing module receives iterative partial responses from storageunits of the second sub-set of the plurality of storage units and theprocessing module processes the group iterative partial response and theiterative partial responses to produce an iterative response (e.g., therecovered data).

The method described above in conjunction with the processing module canalternatively be performed by other modules of the dispersed storagenetwork or by other devices. In addition, at least one memory section(e.g., a computer readable storage medium) that stores operationalinstructions can, when executed by one or more processing modules of oneor more computing devices of the dispersed storage network (DSN), causethe one or more computing devices to perform any or all of the methodsteps described above.

FIG. 43A is a schematic block diagram of another embodiment of adispersed storage network (DSN) that includes a plurality of userdevices 1-U, a plurality of distributed storage and task (DST)processing units 1-100, the network 24 of FIG. 1, and a DST execution(EX) unit set 470. The DST execution unit set 470 includes a set of DSTexecution units 1-n. Each DST execution unit may be implementedutilizing the DST execution unit 36 of FIG. 1. Each user device may beimplemented utilizing at least one of user device 12 of FIG. 1 and userdevice 14 of FIG. 1. Each DST processing unit may be implementedutilizing the DST processing unit 16 of FIG. 1.

The DSN functions to utilize multiple data access resources (e.g., theDST processing units) when accessing data stored in the DSN. In anexample of operation of utilizing the multiple data access resources, aDST processing unit determines whether to update naming affiliationinformation 478 that associates index node index key range assignmentsof a dispersed hierarchical index to the plurality of DST processingunits 1-100. The determining includes at least one of indicating toupdate based on detecting a branching factor change (e.g., a number ofnodes at a level below a reference node), detecting a change in a numberof available DST processing units, and interpreting performanceinformation of one or more DST processing units.

The dispersed hierarchical index includes one root index node, one ormore parent index nodes, and one or more index nodes. Each of the nodes(e.g., root index node, parent index nodes, index nodes) may beimplemented utilizing a data object and includes entries of one or moreof an associated index key range, pointers to other nodes, and pointersto data objects stored in a dispersed storage network (DSN). Suchpointers includes a virtual DSN address (e.g., a source name)corresponding to a storage location the node and/or the data objectwithin the DST execution unit set. Parent index nodes include pointersto child index nodes forming parent-child relationships. Nodes may alsoinclude pointers to sibling level nodes on a common level of the index.Each node is dispersed storage error encoded to produce a set of nodeslices and each set of node slices is stored via slice access 474 in theset of storage units of the DSN at a location corresponding to the DSNaddress of the node.

The dispersed hierarchical index may be constructed and maintain toinclude dimensions associated with one or more index attributes. Indexattributes includes one or more of a maximum number of levels, a minimumnumber of levels (e.g., from the root index node at a top-level to theindex nodes at a lowest level, a maximum number of child nodes in aparent-child node relationship, a minimum number of child nodes in theparent-child node relationship, a maximum number of sibling nodes and acommon level, a minimum number of sibling nodes at the common level, amaximum number of entries in an index node, and a minimum number ofentries in the index node.

The dispersed hierarchical index may be utilized to locate a storagelocation associated with a data object stored in the DST execution unitset of the DSN. For example, starting with the root index node, thedispersed hierarchical index is searched by matching a desired index keyto an index key within an entry of an index node at the lowest level,where the entry of the index node corresponds to the desired dataobject. The search may include accessing successive lower levels of theindex by comparing the desired index key to the index key rangesassociated with nodes between the root index node and the index node ofthe lowest level that is associated with the desire data object. Thelowest level of index nodes includes entries associated with the dataobjects stored in the DSN

Each DST processing unit is associated with an index node index keyrange and may be associated with any level of the dispersed hierarchicalindex. For example, DST processing unit 1 is associated with an indexnode index key range of 0-19 of a maximum of 2000, DST processing unit 2is associated with an index node index key range of 20-39 of the maximumof 2000, etc., through DST processing unit 100 is associated with anindex node index key range of 1980-1999 of the maximum of 2000 when theindex key range at one level below the root node level includes themaximum of 2000 and a mapping scheme includes even distribution ofportions of the index key range.

When updating the naming affiliation information 478, the DST processingunit identifies a number of available DST processing units. Theidentifying includes at least one of initiating a query, receiving aquery response, performing a lookup, and interpreting an error message.Having identified the number of available DST processing units, the DSTprocessing unit determines a reference branching factor of the dispersedhierarchical index. For example, the DST processing unit counts a numberof children nodes one level below the root node as the branching factor.

Having determined the branching factor, the DST processing unitidentifies an index key type associated with the dispersed hierarchicalindex. For example, the DST processing unit accesses a metadata fileassociated with the dispersed particle index to extract the index keytype. Having identified the index key type, the DST processing unitpartitions the branching factor based on the number of available DSTprocessing units in accordance with a partitioning scheme to produce anindex node to DST processing unit mapping. For example, the DSTprocessing unit indicates how many index nodes are to be associated witheach DST processing unit, and which index nodes are to be associatedwith each DST processing unit.

Having partitioned the branching factor, the DST processing unitgenerates the updated naming affiliation information 478 based on theindex node to the DST processing unit mapping and the index key type.For example, the DST processing unit identifies breakpoints in acontinuum of index keys in accordance with the index key type for thebranching factor number of index nodes and associates the breakpointswith each of the available DST processing units to produce the updatednaming affiliation information 478. Having generated the updated namingaffiliation information 478, the DST processing unit facilitatesdistribution of the updated naming affiliation information 478 to one ormore of the plurality of DST processing units and the plurality of userdevices.

With the naming affiliation updated, the DSN facilitates data access 472by the user devices with the DST processing units in accordance with theupdated naming affiliation information 478. As a specific example, auser device 3 selects DST processing unit 4 affiliated with an index key62 based on the index node range of the DST processing unit 4 inaccordance with the updated data affiliation information 478. Havingselected the DST processing unit, the user device 3 exchanges dataaccess 472 (e.g., sends data access requests to the DST processing unit4, receives data access responses from the DST processing unit 4) withthe selected DST processing unit 4. The DST processing unit 4 exchangesslice accesses 474 (e.g., slice access 1-n) with the set of DSTexecution units 1-n to facilitate the data access 472.

FIG. 43B is a flowchart illustrating an example of associating dataaccess resources with an index. The method begins or continues at step480 where a processing module (e.g., of a distributed storage and task(DST) processing unit) determines whether to update naming affiliationinformation that associates index node index key range assignments of adispersed hierarchical index to a plurality of data access resources(e.g., to a plurality of DST processing units). The determining may bebased on one or more of interpreting an update schedule, detecting abranching factor change, detecting a number of available data accessresources, and interpreting performance information.

When updating, the method continues at step 482 where the processingmodule identifies a number of available data access resources. Theidentifying includes at least one of interpreting an error message,initiating a query, receiving a query response, and performing a lookup.The method continues at step 484 where the processing module determinesa branching factor of the dispersed hierarchical index. The determiningincludes at least one of accessing the dispersed hierarchical index andcounting a number of index nodes associated with at least one levelbelow a root node level.

The method continues at step 486 where the processing module identifiesan index key type associated with the dispersed hierarchical index. Forexample, the processing module accesses common index informationassociated with the dispersed hierarchical index to extract the indexkey type. The method continues at step 488 where the processing modulepartitions the branching factor based on the number of available dataaccess resources to produce an index node to data access resourcemapping. For example, the processing module divides the branching factorby the number of available data access resources to produce the indexnode to data access resource mapping.

The method continues at step 490 where the processing module generatesupdated naming affiliation information based on the index node to dataaccess resource mapping and the index key type. For example, theprocessing module identifies index key ranges associated with each ofthe data access resources in accordance with the data access resourcemapping and the index key type. The method continues at step 492 wherethe processing module facilitates data access utilizing the updatednaming affiliation information. For example, the processing moduledistributes the updated naming affiliation information to accessingdevices and to the data access resources. As another example, the accessdevices utilize the updated naming affiliation information to access thedata access resources.

FIG. 44A is a schematic block diagram of another embodiment of adispersed storage network (DSN) that includes a plurality of userdevices 1-U, two or more distributed storage and task (DST) processingunits 1-2, the network 24 of FIG. 1, and a DST execution unit set 494.The DST execution unit set 494 includes a set of DST execution units1-n. Each DST execution unit may be implemented utilizing the DSTexecution unit 36 of FIG. 1. Each user device may be implementedutilizing at least one of user device 12 of FIG. 1 and user device 14 ofFIG. 1. Each DST processing unit may be implemented utilizing the DSTprocessing unit 16 of FIG. 1.

The DSN functions to provide data access 496 to the plurality of userdevices to data stored in the DST execution unit set 494 as sets ofencoded data slices, where virtual DSN addresses of the sets of encodeddata slices is maintained in a dispersed hierarchical index. The DSNfurther functions to update the dispersed hierarchical index that isstored in the DST execution unit set. In an example of operation of theupdating of the dispersed hierarchical index, the DST processing unit 1determines to update an index node of the dispersed hierarchical indexin accordance with a pending update (e.g., identify a new entry,identify a modified entry, and identifying an entry for deletion).Having determined to update the index node, the DST processing unit 1initiates the updating of the index node. For example, the DSTprocessing unit 1 updates the index node to produce an updated indexnode; dispersed storage error encodes the updated index node to create aset of updated index node slices; issues index node access 498 bysending, via the network 24, slice access requests 1-n to the set of DSTexecution units to request storage of the set of updated index nodeslices associated with the updated index node; and receives index nodeaccess 498 as slice access responses 1-n indicating whether the storageof the set of updated index node slices is successful.

When the updating of the index node is not successful (e.g., the DSTprocessing unit 1 interprets the slice access responses and indicatesunsuccessful writing of the updated index node), the DST processing unit1 generates a task entry of a task queue associated with the index node.The DST processing unit 1 generates the entry to include the updatedindex node and/or an update to a portion of the index node. Havinggenerated the task entry, the DST processing unit 1 stores the taskentry in the task queue. For example, the DST processing unit 1generates a DSN address for the task entry by performing a deterministicfunction on a source name of the index node and an increment (e.g.,increment an entry count by one) and stores the task entry using thesource name. The storing includes dispersed storage error encoding thetask entry to produce a set of task slices, generating a set of taskslice names for the set of task slices based on the DSN address of thetask entry, generating task queue access 500 to include a set of writeslice requests 1-n that includes the set of task slices and the set oftask slice names, and sending the set of write slice requests 1-n to theset of DST execution units 1-n.

The DST processing unit 2 subsequently accesses the index node. Havingaccessed the index node, the DST processing unit 2 determines whetherthe task queue associated with the index node includes at least oneentry. The determining includes at least one of interpreting an entrycount from the index node and interpreting results of attempting toaccess a first entry of the task queue.

When the task queue includes the at least one entry, the DST processingunit 2 initiates updating of the index node in accordance with the atleast one entry. For example, the DST processing unit 2 updates theindex node with a recovered updated index node of the entry or arecovered update of the entry to generate a newly updated index node.Having generated the newly updated index node, the DST processing unit 2attempts to store the newly updated index node in the set of DSTexecution units (e.g., issuing write slice requests, receiving writeslice responses). When the updating of the newly updated index node issuccessful, the DST processing unit 2 deletes the at least one entryfrom the task queue associated with the index node. For example, the DSTprocessing unit 2 issues delete slice requests to the set of DSTexecution units, where the delete slice requests includes the set ofslice names associated with the entry of the queue.

FIG. 44B is a flowchart illustrating an example of updating a dispersedhierarchical index. The method begins or continues at step 502 where aprocessing module (e.g., of a distributed storage and task (DST)processing unit) determines to update an index node of a dispersedhierarchical index in accordance with a pending update. The methodcontinues at step 504 where the processing module initiates updating ofthe index node. For example, the processing module generates an updatedindex node, encodes the updated index node to produce a set of indexslices, issues write slice requests to the set of storage units thatincludes the set of index slices, receives write slice responses, anddetermines whether the updating is successful based on the receivedwrite slice responses. For instance, the processing module indicatesthat updating his unsuccessful when not receiving a write thresholdnumber of favorable write slice responses.

When the updating of the index node is not successful, the methodcontinues at step 506 where the processing module generates a task entryof a task queue associated with the index node. For example, theprocessing module generates the task entry to include a pending updateof the index node. The method continues at step 508 where the processingmodule stores the task entry in the task queue. For example, theprocessing module generates a DSN address for the task entry based on aDSN address of the index node, and generates a set of encoded taskslices, generates a set of write slice requests that includes the set ofencoded task slices and slice names derived from the DSN address for thetask entry, and sends the set of write slice requests to the set ofstorage units.

The method continues at step 510 where the processing modulesubsequently accesses the index node. For example, the processing moduleidentifies a DSN address of the index node, issues a set of read slicerequests to the set of storage units utilizing the DSN address of theindex node, receives read slice responses, and decodes index node slicesof the received read slice responses to reproduce the index node.

The method continues at step 512 where the processing module determineswhether the task queue associated with the index node includes at leastone task entry. For example, the processing module interprets an entrycount of the reproduced index node and indicates that the index nodeincludes the at least one task entry when the count is greater thanzero. As another example, the processing module initiates access to afirst task entry and indicates that the at least one task entry isincluded when successfully decoding the first task entry.

When the task queue associated with the index node includes the at leastone task entry, the method continues at step 514 where the processingmodule initiates updating of the index node. For example, for each taskentry of the task queue, a processing module facilitates updating of theindex node in accordance with the task entry. For instance, theprocessing module modifies the reproduced index node in accordance withthe task entry, dispersed storage error encodes the modified index nodeto produce a set of modified index slices, sends the set of modifiedindex slices to the set of storage units, receives write sliceresponses, and interprets the received read slice responses to determinewhether the updating of the index node is successful.

When the updating of the index node is successful, the method continuesat step 516 where the processing module deletes the at least one entryfrom the task queue. For example, the processing module issues a set ofdelete slice requests to a DSN address associated with eachcorresponding successfully updated entry of the task queue.

FIG. 45A is a schematic block diagram of another embodiment of adispersed storage network (DSN) that includes a plurality of storagegenerations 1-G, the distributed storage and task network (DSTN)managing unit 18 of FIG. 1, and the network 24 of FIG. 1. Each storagegeneration includes a set of DST execution (EX) units 1-n. Each DSTexecution unit may be implemented utilizing the DST execution unit 36 ofFIG. 1.

The DSN functions to store data as sets of encoded data slicesassociated with a source address range. The source address rangeincludes a portion of slice names associated with the sets of encodeddata slices. Each storage generation is associated with two states ofreadiness of operation. The two states includes active and inactive. Thestorage generation is available to store and retrieve sets of encodeddata slices when the storage generation is active. The storagegeneration is not available to store and retrieve sets of encoded dataslices when the storage generation is inactive (e.g., dormant and notyet assigned). For example, at a time t0, storage generation 1 is activeand storage generations 2-G are inactive.

When a storage generation is active, the storage generations associatedwith a portion of a source address range. The source address rangeincludes a portion of a range of slice names such that the DSN accessesencoded data slices associated with the range of slice names byutilizing the associated storage generation. The slice name includes apillar index (e.g., 1-n for an information dispersal algorithm (IDA)width of 1), a vault identifier, a generation identifier, and a sourcefield. The source field may include an object number associated with adata object for storage and a segment number based on divisions of thedata object are required to produce a plurality of data segments. Forexample, the storage generation 1, at time t0, is associated with anentire source address range of 0-9 such that all encoded data slicesassociated with the source address range 0-9 are accessed utilizing thestorage generation 1. While a first-generation of data is being storedfor a vault Z, the DST execution unit 1 of the storage generation 1 isassociated with encoded data slices with slice names ranging fromP1-VZ-G1-S0 through P1-VZ-G1-S9, the DST execution unit 2 of the storagegeneration 1 is associated with encoded data slices with slice namesranging from P2-VZ-G1-S0 through P2-VZ-G1-S9, etc.

In an example of operation, the DSTN managing unit 18 determines toestablish a first storage generation. The determining may be based onone or more of receiving a manager input, interpreting a schedule,receiving and activation request, interpreting configurationinformation, detecting that a new set of storage units is available, anddetecting that additional storage capacity is required (e.g., anotherstorage generation utilization level compares unfavorably to a maximumstorage generation utilization threshold level).

When determining to establish the first storage generation, the DSTNmanaging unit 18 assigns storage parameters for at least one vault to beassociated with the storage generation. The storage parameters includesone or more of a vault ID, and IDA type, and IDA width, a writethreshold number, a read threshold number, a rebuilding thresholdnumber, and a decode threshold number. The assigning includes one ormore of receiving a manager input, interpreting a system registry,estimating DSN performance, and interpreting a DSN performance goallevel. For example, the DSTN managing unit 18 establishes the storageparameters to include a vault ID of Z based on a manager input.

Having assigned the storage parameters, the DSTN managing unit 18determines a generation number and a source address range to generationmap for the storage generation. For example, the DSTN managing unit 18determines generation 1 when establishing a first storage generation. Asanother example, the DSTN managing unit 18 determines a source addressrange of 0-9 mapped to the storage generation 1 based on a managerinput.

Having determined the generation number and the source address range togeneration map, the DSTN managing unit 18 issues and assignment messageto a set of DST execution units associated with the storage generation,where the message includes one or more of the generation number, sourceaddress range, identifiers of the DST execution units, and a portion ofthe assigned a storage parameters. For example, the DSTN managing unit18 sends, via the network 24, an assignment message 1 to the set of DSTexecution units 1-n of the storage generation 1 to associate the set ofDST execution units with the source address range of 0-9, for generation1 for vault Z. The method to add a new storage generation is discussedin greater detail with reference to FIG. 45B

FIG. 45B is a schematic block diagram of a plurality of storagegenerations 1-4 activated over times t0-t3 by the DSTN managing unit 18of FIG. 45A in accordance with a storage generation activation scheme.In an example of operation of the activation of the storage generations,the DSTN managing unit 18 determines, to add another storage generationto one or more current storage generations. The determining may be basedon one or more of detecting an unfavorable storage utilization level,detecting an unfavorable level of input/output operations, detecting anunfavorable number of metadata objects stored in the one or more currentstorage generations, receiving a manager input, interpreting a schedule,receiving an activation request, interpreting configuration information,detecting that a new set of storage units is available, and detectingthat additional storage capacity is required.

Having determined to add another storage generation, the DSTN managingunit 18 obtains the source address range to generation map. Theobtaining includes at least one of retrieving from a DST execution unit,retrieving from a local memory, and extracting from a system registry.Having obtained the source address range to generation map, the DSTNmanaging unit 18 determines a number of generations when adding ageneration to the one or more current storage generations. Thedetermining may be based on one or more of interpreting a level ofunfavorable storage utilization, interpreting a level of unfavorableinput/output operations, and interpreting a level of number of metadataobjects stored in the one or more current generations. For example, theDSTN managing unit 18 determines to add one new storage generation whenthe level of unfavorable storage utilization is greater than a maximumthreshold level and less than a critical threshold level.

Having determined the number of generations, the DSTN managing unit 18updates the source address range to generation map based on the numberof generations and a deterministic address reallocation scheme, whereeach storage generation is assigned an equal portion of the sourceaddress range in accordance with the number of generations and where,for each current generation, a portion of a current assignment of thesource address range is reassigned to the other storage generation. Forexample, at time t1, the DSTN managing unit 18 updates the sourceaddress range to generation map such that one half of the source addressrange remains with the storage generation 1 and another half of thesource address range is now assigned to a new storage generation 2. Asanother example, at time t2, the DSTN managing unit updates the sourceaddress range to generation map such that each of storage generation 1,2 and new storage generation 3 is associated with one third of thesource address range. As yet another example, at time t3, each storagegeneration is associated with one fourth of the source address range.

Having updated the source address range to generation map, the DSTNmanaging unit 18 facilitates distribution of the updated source addressrange to generation map each of the other generations and the one ormore current generations. For example, the DSTN managing unit 18 issuesassignment messages 520 to the storage generations, where the assignmentmessages 520 includes the updated source address range of generationmap.

Having distributed the updated source address range to generation map,the DSTN managing unit 18 facilitates migration of encoded data slicesfrom each of the one or more current storage generations to a the otherstorage generations in accordance with the updated source address rangeto generation map. The facilitation includes at least one of retrievingand starring slices, sending a request to each other storage generationto issue a read slice requests, and issuing a request to each of the oneor more current storage generations to issue a write slice requests. Forexample, at time t1, one half of the slice is stored in the storagegeneration 1 are migrated to storage generation 2. As another example,at time t2, one third of the slices stored in the storage generation 1are migrated to the storage generation 3 and one third of the slicesstored in the storage generation 2 are migrated to the storagegeneration 3. As yet another example, at time t3, one fourth of theslices stored in the storage generation 1 are migrated to the storagegeneration 4, one fourth of the slices stored in the storage generation2 are migrated to the storage generation 4, and one fourth of the slicesstored in the storage generation 3 are migrated to the storagegeneration 4.

FIG. 45C is a flowchart illustrating an example of adding a storagegeneration to a dispersed storage network (DSN). The method begins orcontinues at step 522 where a processing module (e.g., of a distributedstorage and task network (DSTN) managing unit) determines to add anotherstorage generation to one or more current storage generations. Thedetermining may be based on one or more of detecting an unfavorablestorage utilization level, detecting an unfavorable level ofinput/output operations, and detecting an unfavorable number ofmeta-data objects stored in the one or more current generations.

The method continues at step 524 where the processing module obtains asource address range to generation map associated with the one or morecurrent storage generations. The obtaining includes at least one ofretrieving from a storage generation, extracting from a system registry,initiating a query, and receiving a query response.

The method continues at step 526 where the processing module determinesa number of storage generations resulting from adding the other storagegeneration. For example, the processing module adds a number of currentgenerations from the source address range to generation map and a numberof new generations to produce a number of generations N.

The method continues at step 528 where the processing module updates thesource address range to generation map based on the number of storagegenerations and a deterministic address reallocation scheme. Forexample, the processing module applies the deterministic addressreallocation scheme to the address range to provide equal sized addressranges. For instance, the total range is divided by N to produce theportion for each generation such that equal sized portions of theprevious address range assignments are assigned to the new generation(e.g., 1/N from each). The address reallocation scheme may furtherinclude utilizing contiguous address ranges one possible.

The method continues at step 530 where the processing module facilitatesdistribution of the updated source address range to generation map toeach of the storage generations. For example, the processing modulepublishes the map to all generations and adds the map to system registryinformation for future publishing. The method continues at step 532where the processing module facilitates migration of slices from each ofthe one or more current storage generations to the other storagegeneration in accordance with the updated source address range togeneration map. For example, the processing module sends migrationrequests to the one or more current generations. As another example, theprocessing module sends a migration request to the other storagegeneration where the migration message includes instructions to issue aread slice requests to the one or more current storage generations foraddress ranges of the slices for migration.

FIG. 46A is a schematic block diagram of another embodiment of adispersed storage network (DSN) that includes the network 24 of FIG. 1,and a distributed storage and task (DST) execution (EX) unit set 534.The DST execution unit set 534 includes a set of DST execution units1-n. Each DST execution unit may be implemented utilizing the DSTexecution unit 36 of FIG. 1. The DSN functions to store criticalinformation for subsequent retrieval. The critical information includesone or more of software, a security credential, a certificate chain, anencryption key, an encryption keys seed, configuration information,operational parameters, an access control list, system registryinformation, system management information, and any other informationthat is critical to the operation of the DSN.

An example of operation to retrieve previously stored criticalinformation, the DST execution unit 1 determines to externally acquirethe critical information. The determining may be based on one or more ofdetecting missing previously locally stored critical information,detecting a corrupted critical information, and identifying a need forthe critical information. For example, the DST execution unit 1determines to externally acquire the critical information when the needfor the critical information is identified and the critical informationis not available in the DST execution unit 1 (e.g., never storedlocally).

Having determined to externally acquire the critical information, theDST execution unit 1 identifies a quorum number of candidate devicesassociated with storage of the critical information, where the quorumnumber of candidate devices may be storing duplicate copies of thecritical information. The identifying includes at least one ofinterpreting a system registry information, accessing a list, initiatinga query, receiving a query response, and determining a minimum number ofdesired candidate devices to achieve a retrieval reliability goal level.For example, the DST execution unit 1 identifies each other DSTexecution unit of the set of DST execution units as the quorum number ofcandidate devices when a list of candidate devices indicates the set ofDST execution units.

Having identified the quorum number of candidate devices, the DSTexecution unit 1 selects devices from the quorum number of candidatedevices for a critical information query. The selecting may be based onone or more of a device performance level, a device level of trustindicator, historical device response information, a predetermination, arequest, device availability information, and a minimum number ofselected devices. For example, the DST execution unit 1 selects DSTexecution units 2-n when each DST execution unit is associated with alevel of trust that is greater than a minimum trust threshold level.

Having selected the devices, DST execution unit 1 issues the criticalinformation query to the selected devices. For example, the DSTexecution unit 1 issues, via the network 24, critical informationrequests 536 (e.g., critical information requests 2-n) to the DSTexecution units 2-n. Each of the DST execution units authenticates andauthorizes a received critical information request 536 and, whenauthorized and authenticated, issues a critical information response 538to the DST execution unit 1.

The DST execution unit 1 receives critical information responses 538from at least some of the selected devices. For example, the DSTexecution unit 1 receives critical information responses 2-n. Havingreceived the critical information responses 538, the DST execution unit1 identifies two or more favorably comparing (e.g., received criticalinformation is substantially the same) received critical informationresponses.

Having identified the two or more favorably comparing received criticalinformation responses, the DST execution unit 1 compares a number of thetwo or more favorably comparing received critical information responsesto a minimum threshold number. When the comparison is favorable (e.g.,the number is greater than the minimum threshold number), the DSTexecution unit 1 indicates that the critical information of the two ormore favorably comparing received critical information responses isvalid. Having identified the valid critical information, the DSTexecution unit 1 utilizes the valid critical information. Havingutilized the valid critical information, the DST execution unit 1 mayimmediately delete the valid critical information. For example, the DSTexecution unit 1 deletes the valid critical information that includes anaccess control list when processing an access request has beencompleted.

FIG. 46B is a flowchart illustrating an example of acquiring criticalinformation. The method begins or continues at step 540 where aprocessing module (e.g., of a distributed storage and task (DST)execution unit) determines to externally acquire critical information.The determining may be based on one or more of receiving a request forthe critical information, detecting a corrupted locally stored criticalinformation, detecting missing critical information, and detecting achange in the critical information.

The method continues at step 542 where the processing module identifiescandidate devices, where each candidate device may store a copy of thecritical information. The identifying includes one or more ofidentifying affiliated devices (e.g., other DST execution units),identifying trusted devices, receiving a list, initiating a query, andreceiving a query response. The method continues at step 544 where theprocessing module selects a quorum number of the identified candidatedevices. The selecting includes identifying the quorum number from asystem registry, identifying best-performing devices, identifyingdevices associated with the critical information, identifying mosttrusted devices, and identifying most available devices.

The method continues at step 546 where the processing module issuescritical information requests to the selected quorum number ofidentified devices. For example, the processing module generates thecritical information request to include an identifier of the criticalinformation and sends the critical information request to the selectedquorum number of identified devices. The method continues at step 548where the processing module receives critical information responses.

The method continues at step 550 where the processing module identifiesfavorably comparing critical information responses. For example, theprocessing module indicates that two critical information responsesfavorably compare when critical information of the two criticalinformation responses is substantially the same. The method continues atstep 552 where the processing module indicates valid recovery criticalinformation when a number of the favorably comparing criticalinformation responses compares favorably to a minimum threshold level.For example, the processing module obtains the minimum threshold level(e.g., retrieve, determine as a majority number of the quorum number),compares the number and threshold, and indicates valid when the numberis greater than the minimum threshold level.

The method continues at step 554 where the processing module utilizesthe valid recovery critical information. For example, the processingmodule stores the valid recovery critical information in a local memoryand invokes further processing that utilizes the valid recovery criticalinformation. Alternatively, or in addition to, the processing moduledeletes the locally stored valid recovery critical information whendetermining that the further processing has been completed and thecritical information is to be deleted.

FIGS. 47A and 47B are a schematic block diagram of another embodiment ofa dispersed storage network (DSN) that includes two or more distributedstorage and task (DST) client modules A, B, etc., the network 24 of FIG.1, and a DST execution (EX) unit set 560. The DST execution unit set 560includes a number of DST execution units in accordance with dispersalparameters of an information dispersal algorithm (IDA). For example, theDST execution unit set 560 includes five DST execution units 1-5 when anIDA with is five. Each DST execution unit may be implemented utilizingthe DST execution unit 36 of FIG. 1. Hereafter, each DST execution unitmay be interchangeably referred to as a storage unit and the set of DSTexecution units may be interchangeably referred to as a set of storageunits. Each DST client module may be implemented utilizing the DSTclient module 34 of FIG. 1.

The DSN functions to resolve write request conflicts arising fromsubstantially concurrent storage of a data object in the set of DSTexecution units 1-5 utilizing a multi-phase storage process. Inparticular, each of the DST client modules A, B, C, D, etc., function toresolve the write request conflicts while storing the data object in theDST execution unit set 560. The multiphase storage process includes awriting phase where a set of encoded data slices are sent to the storageunits that provide a temporary locking of received encoded data slices,a committing phase where encoded data slices received by the storageunits are made available for retrieval (e.g., committed) when a writethreshold number of the set of encoded data slices have been received bythe set of storage units, and a finalizing phase 2 and the multiphasestorage process and the locking of the received encoded data slicesenabling subsequent updating of stored data.

FIG. 47A illustrates steps of an example of operation of the resolvingof the write request conflicts where the DST client module A receives astore data request foo that includes data object foo of a revision A forstorage. Having received the data object foo for storage, the DST clientmodule A issues, via an interface associated with the DST client moduleA and the network 24, a write request for a dispersed storage errorencoded version of the data object foo to the storage units of the DSN,where substantially concurrent write requests (e.g., from the DST clientmodules B, C, D, etc.) regarding the data object includes the writerequest. The issuing of the write request includes the DST client moduleA dispersed storage error encoding the data object foo to produce aplurality of sets of encoded data slices. Having produced the pluralityof sets of encoded data slices, the DST client module A generates aplurality of sets of slice names corresponding to the data object foo.Having produced the plurality of sets of slice names, the DST clientmodule A generates one or more sets of write slice requests thatincludes the plurality of sets of encoded data slices and the pluralityof sets of slice names. For example, the DST client module A generateswrite slice requests A1-A5. Having generated the one or more sets ofwrite slice requests, the DST client module A sends, via the network 24,write slice requests A1-A5 to the set of DST execution units 1-5.

Substantially simultaneously, at least the DST client module B receivesanother store data request foo that includes a revision B (e.g., earlieror later version as compared to revision A) of the data object foo. In asimilar fashion to the producing of the write slice requests by the DSTclient module A, the DST client module B generates another set of writeslice requests B1-B5 that includes another plurality of sets of encodeddata slices and another plurality of sets of slice names, where theother plurality of sets of slice names is substantially the same as theplurality of sets of slice names associated with the write slicerequests A1-A5. Having produced the set of write slice requests B1-B5,the DST client module B sends, via the network 24, the set of writeslice requests B1-B5 to the set of DST execution units 1-5.

Write contention may occur between the writing of the set of write slicerequests A1-A5 and the set of write slice requests B1-B5. Each DSTexecution unit receiving write slice requests receives a first writeslice request of write slice request A and B and a second write slicerequest of the write slice requests A and B subsequent to the receivingof the first write slice request, where the first write slice request isassociated with locking and associated slice name to enable furthersteps of writing and the second write slice request is associated with aconflict error. For example, DST execution unit 1 receives the writeslice request A1 as the first write slice request and associates thewrite slice request A1 with locking and receives the write slicerequests B1 as the second write slice request and associates the writeslice requests B1 with the conflict error when the write slice requestA1 is already associated with the locking.

The writing phase of the DST client module A and the writing phase ofthe DST client module B may advance to the committing phase when eitherof the DST client module A or B receives an indication that acorresponding write threshold number of encoded data slices areassociated with locks. As a further example of locking during thewriting phase of the multiphase storage process, the DST client module Ais associated with locking of encoded data slices 1, 2, and 3 while theDST client module B is associated with locking of encoded data slices 4,and 5. As such, a temporary stalemate has occurred when none of the DSTclient modules achieves locking of the write threshold number of encodeddata slices due to the write conflict.

FIG. 47B illustrates further steps of the example of operation of theresolving of the write request conflicts where, in response to the writerequest, the DST client module A receives write responses (e.g., writeslice responses A1-A5) from at least some of the DST execution units,where each of the write responses includes either a lock indication or anon-lock indication and conflict information. For example, the DSTclient module A receives write slice responses A1-A3 including the lockindication and receives write slice responses A4-A5 with the non-lockindication and the conflict information.

The conflict information includes one or more of identity of a secondwrite request (e.g., write slice request B4 or B5) for the dispersedstorage error encoded version of the data object issued by a secondcomputing device (e.g., DST client module B) that has received the lockindication, identity of the second computing device (e.g., DST clientmodule B), identity of a third write request for the dispersed storageerror encoded version of the data object issued by a third computingdevice (e.g., DST client module C) that did not receive the lockindication, identity of the third computing device (e.g., DST clientmodule C), and information regarding write request processingcharacteristics of the one of the at least some of the storage units.The information regarding the write request processing characteristicsincludes one or more of duration of the lock, number of conflictsgenerated over various time frames, number of unique requesters over thevarious time frames, average lock duration for a previous lock,timestamps associated with receipt of multiple write requests, orderingof receipt of the multiple write requests, and a requesting entitypriority level.

Having received the write responses, the DST client module A determineswhether at least a write threshold number of write responses have beenreceived that include the lock indication. For example, the DST clientmodule A indicates that less than the at least a write threshold numberof write responses have been received that includes the lock indicationwhen only receiving the write slice responses A1-A3 (e.g., 3 responses)that includes the lock indication and the write threshold number is 4.

When less than the at least a write threshold number of write responseshave been received that include the lock indication, the DST clientmodule processes the conflict information to identify one or more otherwrite requests of the substantially concurrent write requests that havea higher priority than the write request. As a specific example, the DSTclient module B determines that, in response to each of the one or moreother write requests, a greater number of lock indications were receivedthan were received for the write request (e.g., noting that the DSTclient module A received three lock indications while the DST clientmodule B received only to lock indications). As another specificexample, the DST client module determines that, in response to one ofthe one or more other write requests, an equal number of lockindications were received as were received for the write request (e.g.,a tie), executes a retry tie-breaking protocol when the equal number oflock indications were received for the one of the one or more otherwrite requests as were received for the write request.

The retry tie-breaking protocol includes the DST client module grantingpriority to the one of the one or more other write requests when anothercomputing device (e.g., another DST client module) associated with theone of the one or more other write requests has a higher device prioritythan the computing device. For example, the DST client module B grantspriority to the requests of the DST client module A when, in anotherscenario, a tie has occurred. Alternatively, the retry tie-breakingprotocol includes the DST client module interpreting the conflictinformation from the storage units of the at least some of the storageunits that did not provide the lock indication to the write request ofthe computing device or to the one or more other write requests of theother computing devices to determine a retry priority between the writerequest and the one or more other write requests. For example, the DSTclient module determines whether the write requests of the DST clientmodule are ahead in priority or behind in priority of the other DSTclient modules.

Having identified the one or more other write requests of thesubstantially concurrent write requests that have a higher priority thanthe write request, the DST client module A establishes a write requestretry time frame based on the one or more other write requests that havethe higher priority. For example, the DST client module A establishesthe write request retry time frame based on an estimation of when thetwo write slice requests of the DST client module B that are associatedwith the lock condition are released (e.g., timeout within the storageunit, storage unit receives an undue request from the DST client moduleB).

Having established the write request retry time frame, at expiration ofthe write request retry time frame, the DST client module A issues aretry write request for the dispersed storage error encoded version ofthe data object. For example, the DST client module A issues, via thenetwork 24, retry write slice requests A4 and A5 to the DST executionunits 4 and 5 when the DST client module A determines that the locks onthe encoded data slices 1-3 associated with DST execution units 1-3 willnot expire while attempting the retry write request. As another example,the DST client module A issues, via the network 24, retry write slicerequests A1-A5 when the DST client module A determines that the locks onthe encoded data slices 1-3 will likely expire while attempting theretry write request.

Having issued the retry write request, the DST client module A receives,in response to the retry write request, retry write responses from atleast some of the storage units, where each of the retry write responsesincludes either the lock indication or the non-lock indication andupdated conflict information. For example, the DST client module Areceives retry write responses that includes another write sliceresponse A4 and another write slice response A5, where at least onewrite slice response includes the lock indication.

Having received the retry write responses, the DST client module Adetermines whether at least a write threshold number of retry writeresponses (e.g., write slice responses from the write slice requestsand/or the retry write slice requests) have been received that includethe lock indication. For example, the DST client module A indicates thatthe write threshold number of retry write responses has been receivedwhen receiving the write slice responses A1-A5 indicating the lockcondition and when receiving the other write slice responses A4-A5indicating at least one more lock condition. When the at least a retrywrite threshold number of retry write responses have been received thatinclude the lock indication, the DST client module A issues a commitcommand to the at least some of the storage units. For example, the DSTclient module A issues, via the network 24, commit transaction requeststo each DST execution unit of the DST execution unit set 560 to executethe commit phase. Subsequent to confirmation of receipt of the writethreshold number of the commit transaction requests by the set of DSTexecution units, the DST client module A issues, via the network 24,finalize transaction requests to the DST execution units of the DSTexecution unit set 560 to complete the finalize phase.

FIG. 47C is a table illustrating an example of resolving write requestconflicts. In particular, the table represents steps of another exampleof operation of the resolving of the write request conflicts where 4 DSTprocessing modules A-D are contending to write the data object to theset of storage units 1-5 of FIGS. 47A-B. The table includes a requestsequencing section 562, a lock information section 564, and a deducepriority section 566. The request sequencing section 562 includes astorage unit field 568, a lock owner field 570, and a received order ofrequests field 572. The lock information section 564 includes fields forpriority order responses each of the DST processing modules A-D. Thededuced priority section 566 includes fields for self ranking andpriority order deduction by each of the DST processing modules A-D.

In the example of operation, entries of the storage unit field 568indicates a particular storage unit of the storage units 1-5. Entries ofthe lock owner field 570 indicates a locking selection by acorresponding storage unit. For example, storage unit 2 returns a writeresponse that includes the lock indication for the DST processing moduleB. Entries of the received order of requests field 572 indicates anordering of received write requests from the DST processing modules by acorresponding storage unit. For example, storage unit 2 receives a writeslice request from DST processing module B first, a write slice requestfrom the DST processing module A second, a write slice request from theDST processing module D third, and a write slice request from the DSTprocessing module C fourth.

When receiving a write request, each storage unit issues a writeresponse to a corresponding requesting DST processing module. Whenreceiving the first write slice request, the storage unit issues a writeresponse that includes the lock indication (e.g., indicating that atthis point in time the corresponding DST processing module owns the lockand there is no contention). For example, the storage unit 2 receivesthe first write slice request from the DST processing module B andissues a first write slice response to the DST processing module Bindicating that the DST processing module B owns the lock. Whenreceiving the second write slice request, the storage unit issues asecond write slice response that includes the non-lock indication andthe conflict information. For example, the storage unit 2 receives thesecond write slice request from the DST processing module A and issues asecond write slice response to the DST processing module A indicating,where the second write slice response includes the non-like indicationand the conflict information, where the conflict information indicatesthat DST processing module B owns the lock and that the DST processingmodule A is associated with the second write slice request (e.g., asecond priority).

Each DST processing module receiving a write slice response interpretsone or more of the lock indication, the non-lock indication, and theconflict information to deduce a priority ranking vis-a-vis other DSTprocessing modules. The deducing includes processing the conflictinformation to identify one or more other write requests of thesubstantially concurrent write requests that have a higher priority thanthe write request. For example, the DST processing module B determinesthat, in response to each of the one or more other write requests, agreater number of lock indications received that were received for thewrite request associated with DST processing module B (e.g., both DSTprocessing modules A and C received two locks while DST processingmodule B only receive one lock).

As another example, the DST processing modules A and C both determinethat, in response to one of the one or more other write requests, anequal number of lock indications were received as were received for thewrite requests associated with the DST processing modules A and C (e.g.,DST processing modules A and C both received two locks). When the equalnumber of lock indications were received, the DST processing modules Aand C both execute a retry tie-breaking protocol. The retry tie-breakingprotocol includes granting priority to the one of the one or more otherwrite requests when another computing device associated with the one ofthe one or more other write requests has a higher device priority thanthe computing device. For instance, the DST processing module C deducesthat the DST processing module A has higher priority based on the writeslice response issued to the DST processing module C (e.g., priorityorder response B, A, D, C) and associates a second priority level withthe DST processing module C. In a similar instance, the DST processingmodule A also deduces that the DST processing module A has the higherpriority and associates a first priority level with the DST processingmodule A.

The DST processing module B interprets the five write slice responsesthat the DST processing module B received from the five storage units todeduce a rank of 3 when the lock indications indicate that the DSTprocessing modules A and C each own two locks and the DST processingmodule B has a greater priority as indicated by the priority orderresponses than the DST processing module D. The DST processing module Binterprets the five write responses that the DST processing module Breceived from the five storage units to deduce a rank of 4 when the lockindications indicate that the DST processing modules A and C each ownthe two locks and the priority order of the DST processing module B isalways greater than that of the DST processing module D.

Having deduced a priority ranking, each DST processing moduleestablishes a write request retry time frame based on the one or moreother write requests that have the higher priority and at the expirationof the write request retry time frame, issue a retry write request toone or more the storage units. The establishing of the write requestretry time frame may be further based on one or more aspects of theconflict information. For example, the DST processing module establishesthe write request retry time frame based on one or more of an estimatedtime to process the multiphase write process, an estimated lockduration, a lock timeout duration, a historical rate of conflicts, and ahistorical probability of success of each retry. For instance, the DSTprocessing module A establishes an associated write request retry timeframe to be substantially the same as the estimated time to execute themultiphase write process when deducing the first priority ranking, theDST processing module C establishes an associated write request retrytime frame to be twice the estimated write time to execute themultiphase write process when deducing the second priority ranking, theDST processing module B establishes an associated write request retrytime frame to be three times the estimated write time to execute themultiphase write process when deducing the third priority ranking, andthe DST processing module D establishes an associated write requestretry time frame to be four times the estimated write time to executethe multiphase write process when deducing the fourth priority ranking.As such, the method may provide an improved level of system operation toefficiently process the contending write requests in a sequentialefficient manner without further contention.

FIG. 47D is a flowchart illustrating an example of resolving writerequest conflicts regarding a data object arising from substantiallyconcurrent write requests. In particular, a method is presented for usein conjunction with one or more functions and features described inconjunction with FIGS. 1-39, 47A-C, and also FIG. 47D. The method beginsat step 580 where a processing module of a computing device (e.g., adistributed storage and task processing module) of one or more computingdevices of a dispersed storage network (DSN) issues a write request fora dispersed storage error encoded version of the data object to storageunits of the DSN. For example, the computing device dispersed storageerror encodes the data object to produce a plurality of sets of encodeddata slices and sends the plurality of sets of encoded data slices to aset of storage units of the DSN.

The method continues at step 582 where the computing device receives, inresponse to the write request, write responses from at least some of thestorage units, where each of the write responses includes either a lockindication or a non-lock indication and conflict information. The methodcontinues at step 584 where computing device determines whether at leasta write threshold number of write responses have been received thatinclude the lock indication.

When less than the at least a write threshold number of write responseshave been received that include the lock indication, the methodcontinues at step 586 where the computing device processes the conflictinformation to identify one or more other write requests of thesubstantially concurrent write requests that have a higher priority thanthe write request. For example, the computing device determines that, inresponse to each of the one or more other write requests, a greaternumber of lock indications were received than were received for thewrite request. As another example, the computing device determines that,in response to one of the one or more other write requests, an equalnumber of lock indications were received as were received for the writerequest. When the equal number of lock indications were received for theone of the one or more other write requests as were received for thewrite request, the computing device executes a retry tie-breakingprotocol. For example, the computing device grants priority to the oneof the one or more other write requests when another computing deviceassociated with the one of the one or more other write requests has ahigher device priority than the computing device. As another example,the computing device interprets the conflict information from thestorage units of the at least some of the storage units that did notprovide the lock indication to the write request of the computing deviceor to the one or more other write requests of the other computingdevices to determine a retry priority between the write request and theone or more other write requests.

The method continues at step 588 where the computing device establishesa write request retry time frame based on the one or more other writerequests that have the higher priority. At expiration of the writerequest retry time frame, the method continues at step 590 where thecomputing device issues a retry write request for the dispersed storageerror encoded version of the data object. The method continues at step592 where the computing device receives, in response to the retry writerequest, retry write responses from at least some of the storage units,where each of the retry write responses includes either the lockindication or the non-lock indication and updated conflict information.

The method continues at step 594 where the computing device determineswhether at least a write threshold number of retry write responses havebeen received that include the lock indication (e.g., from a totalnumber of write responses and retry write responses that include thelock indication). When the at least a retry write threshold number ofretry write responses have been received that include the lockindication, the method continues at step 596 where the computing deviceissues a commit command to the at least some of the storage units.

The method described above in conjunction with the processing module canalternatively be performed by other modules of the dispersed storagenetwork or by other devices. In addition, at least one memory section(e.g., a computer readable storage medium) that stores operationalinstructions can, when executed by one or more processing modules of oneor more computing devices of the dispersed storage network (DSN), causethe one or more computing devices to perform any or all of the methodsteps described above.

FIG. 48A is a schematic block diagram of another embodiment of adispersed storage network (DSN) that includes a plurality of distributedstorage and task (DST) client modules 1-D, the distributed storage andtask network (DSTN) managing unit 18 of FIG. 45A, the network 24 of FIG.1, and the plurality of storage generations 1-G of FIG. 45A. The DSNfunctions to ingest large amounts of data storage in one or more of thestorage generations and to activate storage generations in accordancewith the ingesting of the data. For example, the DST client module 1receives ingestion data 1, dispersed storage error encodes the ingestiondata to produce sets of encoded data slices, and stores the sets ofencoded data slices in previously activated storage generation 1.

In an example of operation, the DSTN managing unit 18 obtains a storageutilization level for each currently active storage generation. Theobtaining includes at least one of issuing a storage utilization levelrequest, receiving a storage utilization level response, interpreting anerror message, interpreting a DSN log, interpreting storage indicatorswithin a dispersed hierarchical index, and performing a lookup.

Having obtained the storage utilization level, the DSTN managing unit 18obtains a data ingestion rate for each of the currently active storagegenerations. The obtaining includes at least one of issuing a dataingestion rate request, receiving a data ingestion rate response,interpreting the DSN log, interpreting storage indicators within adispersed hierarchical index, performing a lookup, issuing a query toone or more DST client modules, receiving a query response from at leastone DST client module, and performing a lookup.

Having obtained the data ingestion rate, the DSTN managing unit 18determines whether to activate one or more other storage generationsbased on the storage utilization level and the data ingestion rate. Forexample, the DSTN managing unit 18 indicates to activate an additionalstorage generation when the storage utilization level is greater than amaximum storage utilization threshold level. As another example, theDSTN managing unit 18 indicates to activate the additional storagegeneration when the data ingestion rate is greater than a maximum dataingestion threshold level.

When activating the one or more other storage generations, the DSTNmanaging unit 18 determines a number of storage generations to activatebased on one or more of the storage utilization level, the dataingestion rate, and the maximum data ingestion threshold level. Forexample, the DSTN managing unit 18 determines to activate two or moregenerations when the data ingestion rate is greater than the maximumdata ingestion threshold level. As another example, the DSTN managingunit 18 estimates a number of required generation such that a maximumdata ingestion rate threshold level is not compromised for any storagegenerations.

Having determined the number of storage generations to activate, theDSTN managing unit 18 issues assignment messages to inactive storagegenerations in accordance with the number of storage generations toactivate, where the assignment messages includes one or more of anindication to activate, an assigned DSN address range, and an amount ofstorage capacity to allocate for storage. For example, the DSTN managingunit 18 issues, via the network 24, assignment messages 2-3 to storagegenerations 2-3 to initiate activation.

FIG. 48B is a flowchart illustrating an example of activating a storagegeneration. The method begins or continues at step 600 where aprocessing module (e.g., of a distributed storage and task network(DSTN) managing unit) obtains a storage utilization level for each ofone or more current storage generations. The obtaining includes at leastone of initiating a query, receiving a query response, performing alookup, and interpreting system activity logs. For each current storagegeneration, the method continues at step 602 where the processing moduleobtains a data ingestion rate. The obtaining includes at least one ofinitiating a query, receiving a query response, performing a lookup, andinterpreting system activity logs.

The method continues at step 604 where the processing module determineswhether to activate one or more other storage generations. For example,the processing module indicates to activate when at least one of thestorage utilization level is greater than a maximum storage utilizationthreshold level and when the data ingestion rate is greater than amaximum data ingestion threshold level.

When activating the one or more other storage generations, the methodcontinues at step 606 where the processing module determines a number ofstorage generations to activate. For example, the processing moduleestimates a number of required generations such that the data ingestionrate for each of the one or more current storage generations in each ofthe one or more other storage generations is less than a low dataingestion threshold level.

The method continues at step 608 where the processing module issues andassignment message to each of one or more inactive storage generationsin accordance with the number of storage generations to activate. Forexample, the processing module generates the assignment message toinclude an assigned DSN address range and amount of storage capacity toallocate, and sends the assignment message to storage units of the oneor more other storage generations.

As may be used herein, the terms “substantially” and “approximately”provides an industry-accepted tolerance for its corresponding termand/or relativity between items. Such an industry-accepted toleranceranges from less than one percent to fifty percent and corresponds to,but is not limited to, component values, integrated circuit processvariations, temperature variations, rise and fall times, and/or thermalnoise. Such relativity between items ranges from a difference of a fewpercent to magnitude differences. As may also be used herein, theterm(s) “operably coupled to”, “coupled to”, and/or “coupling” includesdirect coupling between items and/or indirect coupling between items viaan intervening item (e.g., an item includes, but is not limited to, acomponent, an element, a circuit, and/or a module) where, for indirectcoupling, the intervening item does not modify the information of asignal but may adjust its current level, voltage level, and/or powerlevel. As may further be used herein, inferred coupling (i.e., where oneelement is coupled to another element by inference) includes direct andindirect coupling between two items in the same manner as “coupled to”.As may even further be used herein, the term “operable to” or “operablycoupled to” indicates that an item includes one or more of powerconnections, input(s), output(s), etc., to perform, when activated, oneor more its corresponding functions and may further include inferredcoupling to one or more other items. As may still further be usedherein, the term “associated with”, includes direct and/or indirectcoupling of separate items and/or one item being embedded within anotheritem. As may be used herein, the term “compares favorably”, indicatesthat a comparison between two or more items, signals, etc., provides adesired relationship. For example, when the desired relationship is thatsignal 1 has a greater magnitude than signal 2, a favorable comparisonmay be achieved when the magnitude of signal 1 is greater than that ofsignal 2 or when the magnitude of signal 2 is less than that of signal1.

As may also be used herein, the terms “processing module”, “processingcircuit”, and/or “processing unit” may be a single processing device ora plurality of processing devices. Such a processing device may be amicroprocessor, micro-controller, digital signal processor,microcomputer, central processing unit, field programmable gate array,programmable logic device, state machine, logic circuitry, analogcircuitry, digital circuitry, and/or any device that manipulates signals(analog and/or digital) based on hard coding of the circuitry and/oroperational instructions. The processing module, module, processingcircuit, and/or processing unit may be, or further include, memoryand/or an integrated memory element, which may be a single memorydevice, a plurality of memory devices, and/or embedded circuitry ofanother processing module, module, processing circuit, and/or processingunit. Such a memory device may be a read-only memory, random accessmemory, volatile memory, non-volatile memory, static memory, dynamicmemory, flash memory, cache memory, and/or any device that storesdigital information. Note that if the processing module, module,processing circuit, and/or processing unit includes more than oneprocessing device, the processing devices may be centrally located(e.g., directly coupled together via a wired and/or wireless busstructure) or may be distributedly located (e.g., cloud computing viaindirect coupling via a local area network and/or a wide area network).Further note that if the processing module, module, processing circuit,and/or processing unit implements one or more of its functions via astate machine, analog circuitry, digital circuitry, and/or logiccircuitry, the memory and/or memory element storing the correspondingoperational instructions may be embedded within, or external to, thecircuitry comprising the state machine, analog circuitry, digitalcircuitry, and/or logic circuitry. Still further note that, the memoryelement may store, and the processing module, module, processingcircuit, and/or processing unit executes, hard coded and/or operationalinstructions corresponding to at least some of the steps and/orfunctions illustrated in one or more of the Figures. Such a memorydevice or memory element can be included in an article of manufacture.

The present invention has been described above with the aid of methodsteps illustrating the performance of specified functions andrelationships thereof. The boundaries and sequence of these functionalbuilding blocks and method steps have been arbitrarily defined hereinfor convenience of description. Alternate boundaries and sequences canbe defined so long as the specified functions and relationships areappropriately performed. Any such alternate boundaries or sequences arethus within the scope and spirit of the claimed invention. Further, theboundaries of these functional building blocks have been arbitrarilydefined for convenience of description. Alternate boundaries could bedefined as long as the certain significant functions are appropriatelyperformed. Similarly, flow diagram blocks may also have been arbitrarilydefined herein to illustrate certain significant functionality. To theextent used, the flow diagram block boundaries and sequence could havebeen defined otherwise and still perform the certain significantfunctionality. Such alternate definitions of both functional buildingblocks and flow diagram blocks and sequences are thus within the scopeand spirit of the claimed invention. One of average skill in the artwill also recognize that the functional building blocks, and otherillustrative blocks, modules and components herein, can be implementedas illustrated or by discrete components, application specificintegrated circuits, processors executing appropriate software and thelike or any combination thereof.

The present invention may have also been described, at least in part, interms of one or more embodiments. An embodiment of the present inventionis used herein to illustrate the present invention, an aspect thereof, afeature thereof, a concept thereof, and/or an example thereof. Aphysical embodiment of an apparatus, an article of manufacture, amachine, and/or of a process that embodies the present invention mayinclude one or more of the aspects, features, concepts, examples, etc.,described with reference to one or more of the embodiments discussedherein. Further, from figure to figure, the embodiments may incorporatethe same or similarly named functions, steps, modules, etc., that mayuse the same or different reference numbers and, as such, the functions,steps, modules, etc., may be the same or similar functions, steps,modules, etc., or different ones.

While the transistors in the above described figure(s) is/are shown asfield effect transistors (FETs), as one of ordinary skill in the artwill appreciate, the transistors may be implemented using any type oftransistor structure including, but not limited to, bipolar, metal oxidesemiconductor field effect transistors (MOSFET), N-well transistors,P-well transistors, enhancement mode, depletion mode, and zero voltagethreshold (VT) transistors.

Unless specifically stated to the contra, signals to, from, and/orbetween elements in a figure of any of the figures presented herein maybe analog or digital, continuous time or discrete time, and single-endedor differential. For instance, if a signal path is shown as asingle-ended path, it also represents a differential signal path.Similarly, if a signal path is shown as a differential path, it alsorepresents a single-ended signal path. While one or more particulararchitectures are described herein, other architectures can likewise beimplemented that use one or more data buses not expressly shown, directconnectivity between elements, and/or indirect coupling between otherelements as recognized by one of average skill in the art.

The term “module” is used in the description of the various embodimentsof the present invention. A module includes a processing module, afunctional block, hardware, and/or software stored on memory forperforming one or more functions as may be described herein. Note that,if the module is implemented via hardware, the hardware may operateindependently and/or in conjunction software and/or firmware. As usedherein, a module may contain one or more sub-modules, each of which maybe one or more modules.

While particular combinations of various functions and features of thepresent invention have been expressly described herein, othercombinations of these features and functions are likewise possible. Thepresent invention is not limited by the particular examples disclosedherein and expressly incorporates these other combinations.

What is claimed is:
 1. A method for execution by one or more processingmodules of one or more computing devices of a dispersed storage network(DSN), the method comprises: generating, based on a data object name, afirst retrieval request for retrieving metadata addressing information,wherein the first retrieval request is formatted in accordance with aread request format of the DSN; generating, based on retrieved metadataaddressing information, a second retrieval request for retrievingmetadata, wherein the second retrieval request is formatted inaccordance with the read request format of the DSN; and generating,based on retrieved metadata, a third retrieval request for retrieving atleast a portion of a data object associated with the data object name,wherein the third retrieval request is formatted in accordance with theread request format of the DSN.
 2. The method of claim 1, wherein thegenerating the first retrieval request comprises: performing adeterministic function on the data object name to produce a digitalvalue; using a first portion of the digital value as a generationidentifier of the read request format of the DSN; and using a secondportion of the digital value as an object identifier of the read requestformat of the DSN.
 3. The method of claim 2, wherein the generating thefirst retrieval request comprises: determining a vault identifierassociated with the data object; and using the vault identifier in avault identifier field of the read request format of the DSN.
 4. Themethod of claim 1 further comprises: generating, based on the dataobject name, the first retrieval request by: generating a set of firstlevel read requests for retrieving at least a decode threshold number ofmetadata addressing information slices, wherein the metadata addressinginformation includes addressing information regarding storage of themetadata within the DSN, wherein the metadata addressing information wasdispersed storage error encoded to produce a set of metadata addressinginformation slices, and wherein the decode threshold number of metadataaddressing information slices represents a minimum number of metadataaddressing information slices of the set of metadata addressinginformation slices that is required to recover the metadata addressinginformation; and decoding the least a decode threshold number ofmetadata addressing information slices to recover the metadataaddressing information.
 5. The method of claim 1, wherein the generatingthe second retrieval request comprises: generating, based on themetadata addressing information, a set of second level read requests forretrieving at least a decode threshold number of metadata slices,wherein the metadata includes addressing information regarding storageof a plurality of sets of encoded data slices of the data object withinthe DSN, wherein the metadata was dispersed storage error encoded toproduce a set of metadata slices, and wherein the decode thresholdnumber of metadata slices represents a minimum number of metadata slicesof the set of metadata slices that is required to recover the metadata.6. The method of claim 5 further comprises: decoding the at least adecode threshold number of metadata slices to recover the metadata. 7.The method of claim 1, wherein the generating the second retrievalrequest comprises: extracting a generation identifier and an objectidentifier from the metadata addressing information; determining a vaultidentifier associated with the data object; using the generationidentifier in a generation identifier field of the read request formatof the DSN; using the object identifier in an object identifier field ofthe read request format of the DSN; and using the vault identifier in avault identifier field of the read request format of the DSN.
 8. Themethod of claim 1, wherein the generating the third retrieval requestcomprises: generating, based on the metadata, at least one set of thirdlevel read requests for retrieving at least a decode threshold number ofencoded data slices, wherein the data object was dispersed storage errorencoded to produce a plurality of sets of encoded data slices, andwherein the decode threshold number of encoded data slices represents aminimum number of encoded data slices of a set of the plurality of setsof encoded data slices that is required to recover the portion of thedata object.
 9. A computer readable storage medium comprises: at leastone memory section that stores operational instructions that, whenexecuted by one or more processing modules of one or more computingdevices of a dispersed storage network (DSN), causes the one or morecomputing devices to: generate, based on a data object name, a firstretrieval request for retrieving metadata addressing information,wherein the first retrieval request is formatted in accordance with aread request format of the DSN; generate, based on retrieved metadataaddressing information, a second retrieval request for retrievingmetadata, wherein the second retrieval request is formatted inaccordance with the read request format of the DSN; and generate, basedon retrieved metadata, a third retrieval request for retrieving at leasta portion of a data object associated with the data object name, whereinthe third retrieval request is formatted in accordance with the readrequest format of the DSN.
 10. The computer readable storage medium ofclaim 9, wherein the one or more processing modules functions to executethe operational instructions stored by the at least one memory sectionto cause the one or more computing devices of the DSN to generate thefirst retrieval request by: performing a deterministic function on thedata object name to produce a digital value; using a first portion ofthe digital value as a generation identifier of the read request formatof the DSN; and using a second portion of the digital value as an objectidentifier of the read request format of the DSN.
 11. The computerreadable storage medium of claim 10, wherein the one or more processingmodules functions to execute the operational instructions stored by theat least one memory section to cause the one or more computing devicesof the DSN to generate the first retrieval request by: determining avault identifier associated with the data object; and using the vaultidentifier in a vault identifier field of the read request format of theDSN.
 12. The computer readable storage medium of claim 9 furthercomprises: the at least one memory section stores further operationalinstructions that, when executed by the one or more processing modules,causes the one or more computing devices of the DSN to: generate, basedon the data object name, the first retrieval request by: generating aset of first level read requests for retrieving at least a decodethreshold number of metadata addressing information slices, wherein themetadata addressing information includes addressing informationregarding storage of the metadata within the DSN, wherein the metadataaddressing information was dispersed storage error encoded to produce aset of metadata addressing information slices, and wherein the decodethreshold number of metadata addressing information slices represents aminimum number of metadata addressing information slices of the set ofmetadata addressing information slices that is required to recover themetadata addressing information; and decode the least a decode thresholdnumber of metadata addressing information slices to recover the metadataaddressing information.
 13. The computer readable storage medium ofclaim 9, wherein the one or more processing modules functions to executethe operational instructions stored by the at least one memory sectionto cause the one or more computing devices of the DSN to generate thesecond retrieval request by: generating, based on the metadataaddressing information, a set of second level read requests forretrieving at least a decode threshold number of metadata slices,wherein the metadata includes addressing information regarding storageof a plurality of sets of encoded data slices of the data object withinthe DSN, wherein the metadata was dispersed storage error encoded toproduce a set of metadata slices, and wherein the decode thresholdnumber of metadata slices represents a minimum number of metadata slicesof the set of metadata slices that is required to recover the metadata.14. The computer readable storage medium of claim 13 further comprises:the at least one memory section stores further operational instructionsthat, when executed by the one or more processing modules, causes theone or more computing devices of the DSN to: decode the at least adecode threshold number of metadata slices to recover the metadata. 15.The computer readable storage medium of claim 9, wherein the one or moreprocessing modules functions to execute the operational instructionsstored by the at least one memory section to cause the one or morecomputing devices of the DSN to generate the second retrieval requestby: extracting a generation identifier and an object identifier from themetadata addressing information; determining a vault identifierassociated with the data object; using the generation identifier in ageneration identifier field of the read request format of the DSN; usingthe object identifier in an object identifier field of the read requestformat of the DSN; and using the vault identifier in a vault identifierfield of the read request format of the DSN.
 16. The computer readablestorage medium of claim 9, wherein the one or more processing modulesfunctions to execute the operational instructions stored by the at leastone memory section to cause the one or more computing devices of the DSNto generate the third retrieval request by: generating, based on themetadata, at least one set of third level read requests for retrievingat least a decode threshold number of encoded data slices, wherein thedata object was dispersed storage error encoded to produce a pluralityof sets of encoded data slices, and wherein the decode threshold numberof encoded data slices represents a minimum number of encoded dataslices of a set of the plurality of sets of encoded data slices that isrequired to recover the portion of the data object.
 17. A computingdevice of a group of computing devices of a dispersed storage network(DSN), the computing device comprises: an interface; a local memory; anda processing module operably coupled to the interface and the localmemory, wherein the processing module functions to: generate, based on adata object name, a first retrieval request for retrieving metadataaddressing information, wherein the first retrieval request is formattedin accordance with a read request format of the DSN; generate, based onretrieved metadata addressing information, a second retrieval requestfor retrieving metadata, wherein the second retrieval request isformatted in accordance with the read request format of the DSN; andgenerate, based on retrieved metadata, a third retrieval request forretrieving at least a portion of a data object associated with the dataobject name, wherein the third retrieval request is formatted inaccordance with the read request format of the DSN.
 18. The computingdevice of claim 17, wherein the processing module functions to generatethe first retrieval request by: performing a deterministic function onthe data object name to produce a digital value; using a first portionof the digital value as a generation identifier of the read requestformat of the DSN; and using a second portion of the digital value as anobject identifier of the read request format of the DSN.
 19. Thecomputing device of claim 18, wherein the processing module functions togenerate the first retrieval request by: determining a vault identifierassociated with the data object; and using the vault identifier in avault identifier field of the read request format of the DSN.
 20. Thecomputing device of claim 17, wherein the processing module furtherfunctions to: generate, based on the data object name, the firstretrieval request by: generating a set of first level read requests forretrieving at least a decode threshold number of metadata addressinginformation slices, wherein the metadata addressing information includesaddressing information regarding storage of the metadata within the DSN,wherein the metadata addressing information was dispersed storage errorencoded to produce a set of metadata addressing information slices, andwherein the decode threshold number of metadata addressing informationslices represents a minimum number of metadata addressing informationslices of the set of metadata addressing information slices that isrequired to recover the metadata addressing information; and decode theleast a decode threshold number of metadata addressing informationslices to recover the metadata addressing information.
 21. The computingdevice of claim 17, wherein the processing module functions to generatethe second retrieval request by: generating, based on the metadataaddressing information, a set of second level read requests forretrieving at least a decode threshold number of metadata slices,wherein the metadata includes addressing information regarding storageof a plurality of sets of encoded data slices of the data object withinthe DSN, wherein the metadata was dispersed storage error encoded toproduce a set of metadata slices, and wherein the decode thresholdnumber of metadata slices represents a minimum number of metadata slicesof the set of metadata slices that is required to recover the metadata.22. The computing device of claim 21, wherein the processing modulefurther functions to: decode the at least a second decode thresholdnumber of metadata slices to recover the metadata.
 23. The computingdevice of claim 17, wherein the processing module functions to generatethe second retrieval request by: extracting a generation identifier andan object identifier from the metadata addressing information;determining a vault identifier associated with the data object; usingthe generation identifier in a generation identifier field of the readrequest format of the DSN; using the object identifier in an objectidentifier field of the read request format of the DSN; and using thevault identifier in a vault identifier field of the read request formatof the DSN.
 24. The computing device of claim 17, wherein the processingmodule functions to generate the third retrieval request by: generating,based on the metadata, at least one set of third level read requests forretrieving at least a decode threshold number of encoded data slices,wherein the data object was dispersed storage error encoded to produce aplurality of sets of encoded data slices, and wherein the decodethreshold number of encoded data slices represents a minimum number ofencoded data slices of a set of the plurality of sets of encoded dataslices that is required to recover the portion of the data object.